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SEP A stable election protocol for clustered heterogeneous wireless sensor networks

SEP:A Stable Election Protocol for clustered heterogeneous wireless sensor networks?Georgios Smaragdakis Ibrahim Matta Azer Bestavros

Computer Science Department

Boston University

Boston,MA02215,USA

{gsmaragd,matta,best}@https://www.doczj.com/doc/f912271164.html,

T echnical Report BUCS-TR-2004-022

ABSTRACT

We study the impact of heterogeneity of nodes,in terms of their en-ergy,in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads,aggre-gate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of het-erogeneity which may result from the initial setting or as the oper-ation of the network evolves.We also assume that the sensors are randomly(uniformly)distributed and are not mobile,the coordi-nates of the sink and the dimensions of the sensor?eld are known. We show that the behavior of such sensor networks becomes very unstable once the?rst node dies,especially in the presence of node heterogeneity.Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogene-ity.We propose SEP,a heterogeneous-aware protocol to prolong the time interval before the death of the?rst node(we refer to as stability period),which is crucial for many applications where the feedback from the sensor network must be reliable.SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node.We show by simulation that SEP always prolongs the stability period compared to(and that the average throughput is greater than)the one obtained using current clustering protocols.We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters captur-ing energy imbalance in the network.We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.

1.INTRODUCTION

Motivation:Wireless Sensor Networks are networks of tiny,bat-tery powered sensor nodes with limited on-board processing,stor-age and radio capabilities[1].Nodes sense and send their reports toward a processing center which is called“sink.”Designing pro-tocols and applications for such networks has to be energy aware in order to prolong the lifetime of the network,because the replace-ment of the embedded batteries is a very dif?cult process once these nodes have been installed.Classical approaches like Direct Trans-?This work was supported in part by NSF grants ANI-0095988, ANI-9986397,EIA-0202067,and ITR ANI-0205294.

.mission and Minimum Transmission Energy[9]do not guarantee well balanced distribution of the energy load among nodes of the sensor https://www.doczj.com/doc/f912271164.html,ing Direct Transmission(DT),sensor nodes transmit directly to the sink,as a result nodes that are far away from the sink would die?rst[6].On the other hand,using Mini-mum Transmission Energy(MTE),data is routed over minimum-cost routes,where cost re?ects the transmission power expended. Under MTE,nodes that are near the sink act as relays with higher probability than nodes that are far from the sink.These former nodes tend to die fast.Under both DT and MTE,a part of the?eld will not be monitored for a signi?cant part of the lifetime of the network,and as a result the sensing process of the?eld will be bi-ased.A solution proposed in[7],called LEACH,guarantees that the energy load is well distributed by dynamically created clusters, using cluster heads dynamically elected according to a priori op-timal probability.Cluster heads aggregate reports from their clus-ter members before forwarding them to the sink.By rotating the cluster-head role uniformly among all nodes,each node tends to expend the same energy over time.

Most of the analytical results for LEACH-type schemes are ob-tained assuming that the nodes of the sensor network are equipped with the same amount of energy—this is the case of homogeneous sensor networks.In this paper we study the impact of heterogene-ity in terms of node energy.We assume that a percentage of the node population is equipped with more energy than the rest of the nodes in the same network—this is the case of heterogeneous sen-sor networks.We are motivated by the fact that there are a lot of applications that would highly bene?t from understanding the im-pact of such heterogeneity.One of these applications could be the re-energization of sensor networks.As the lifetime of sensor net-works is limited there is a need to re-energize the sensor network by adding more nodes.These nodes will be equipped with more energy than the nodes that are already in use,which creates het-erogeneity in terms of node energy.Note that due to practical/cost constraints it is not always possible to satisfy the constraints for op-timal distribution between different types of nodes as proposed in [8].

There are also applications where the spatial density of sensors is a constraint.Assuming that with the current technology the cost of a sensor is tens of times greater than the cost of embedded bat-teries,it will be valuable to examine whether the lifetime of the network could be increased by simply distributing extra energy to some existing nodes without introducing new nodes.1

1We also study the case of uniformly distributing such extra energy over all nodes.In practice,however,it maybe dif?cult to achieve

Perhaps the most important issue is that heterogeneity of nodes, in terms of their energy,is simply a result of the network operation as it evolves.For example,nodes could,over time,expend different amounts of energy due to the radio communication characteristics, random events such as short-term link failures or morphological characteristics of the?eld(e.g.uneven terrain).

Our Contribution:In this paper we assume that the sink is not en-ergy limited(at least in comparison with the energy of other sensor nodes)and that the coordinates of the sink and the dimensions of the?eld are known.We also assume that the nodes are uniformly distributed over the?eld and they are not mobile.Under this model, we propose a new protocol,we call SEP,for electing cluster heads in a distributed fashion in two-level hierarchical wireless sensor networks.Unlike prior work(reviewed throughout the paper and in Section7),SEP is heterogeneous-aware,in the sense that election probabilities are weighted by the initial energy of a node relative to that of other nodes in the network.This prolongs the time interval before the death of the?rst node(we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable.We show by simulation that SEP provides longer stability period and higher average throughput than current clustering heterogeneous-oblivious protocols.We also study the sensitivity of our SEP protocol to heterogeneity parame-ters capturing energy imbalance in the network.We show that SEP is more resilient than LEACH in judiciously consuming the extra energy of advanced nodes—SEP yields longer stability region for higher values of extra energy.

Paper Organization:The rest of the paper is organized as follows. Section2provides the model of our setting.Section3de?nes our performance measures.In Section4we address the problem of het-erogeneity in clustered wireless sensor networks,and in Section5 we provide our solution to the problem.Section6presents sim-ulation results.We review related work in Section7.Section8 concludes with directions for future work.

2.HETEROGENEOUS WSN MODEL

In this section we describe our model of a wireless sensor net-work with nodes heterogeneous in their initial amount of energy. We particularly present the setting,the energy model,and how the optimal number of clusters can be computed.

Let us assume the case where a percentage of the population of sensor nodes is equipped with more energy resources than the rest of the nodes.Let m be the fraction of the total number of nodes n,which are equipped withαtimes more energy than the others. We refer to these powerful nodes as advanced nodes,and the rest (1?m)×n as normal nodes.We assume that all nodes are distributed uniformly over the sensor?eld.

2.1Clustering Hierarchy

We consider a sensor network that is hierarchically clustered. The LEACH(Low Energy Adaptive Clustering Hierarchy)proto-col[6]maintains such clustering hierarchy.In LEACH,the clusters are re-established in each“round.”New cluster heads are elected in each round and as a result the load is well distributed and balanced among the nodes of the network.Moreover each node transmits to the closest cluster head so as to split the communication cost to the sink(which is tens of times greater than the processing and opera-tion cost).Only the cluster head has to report to the sink and may expend a large amount of energy,but this happens periodically for such uniform distribution because extra energy could be expressed only in terms of discrete battery units.Even if this is possible,we show in this paper that such fair distribution of extra energy is not

always bene?cial.each node.In LEACH there is an optimal percentage p opt(deter-mined a priori)of nodes that has to become cluster heads in each round assuming uniform distribution of nodes in space[2,3,6,7]. If the nodes are homogeneous,which means that all the nodes in the?eld have the same initial energy,the LEACH protocol guaran-tees that everyone of them will become a cluster head exactly once every1

p opt

rounds.Throughout this paper we refer to this number

of rounds,1

p opt

,as epoch of the clustered sensor network. Initially each node can become a cluster head with a probabil-ity p opt.On average,n×p opt nodes must become cluster heads per round per epoch.Nodes that are elected to be cluster heads in the current round can no longer become cluster heads in the same epoch.The non-elected nodes belong to the set G and in order to maintain a steady number of cluster heads per round,the proba-bility of nodes∈G to become a cluster head increases after each round in the same epoch.The decision is made at the beginning of each round by each node s∈G independently choosing a ran-dom number in[0,1].If the random number is less than a threshold T(s)then the node becomes a cluster head in the current round. The threshold is set as:

T(s)= p opt

1?p opt·(r mod1

p opt

)

if s∈G

0otherwise

(1)

where r is the current round number.The election probability of nodes∈G to become cluster heads increases in each round in the same epoch and becomes equal to1in the last round of the epoch. Note that by round we de?ne a time interval where all clusters members have to transmit to the cluster head once.We show in this paper how the election process of cluster heads should be adapted appropriately to deal with heterogeneous nodes,which means that not all the nodes in the?eld have the same initial energy.

2.2Optimal Clustering

Previous work have studied either by simulation[6,7]or ana-lytically[2,3]the optimal probability of a node being elected as a cluster head as a function of spatial density when nodes are uni-formly distributed over the sensor?eld.This clustering is optimal in the sense that energy consumption is well distributed over all sensors and the total energy consumption is minimum.Such opti-mal clustering highly depends on the energy model we use.For the purpose of this study we use similar energy model and analysis as proposed in[7].

Figure1:Radio Energy Dissipation Model.

According to the radio energy dissipation model illustrated in Figure1,in order to achieve an acceptable Signal-to-Noise Ratio (SNR)in transmitting an L?bit message over a distance d,the en-ergy expended by the radio is given by:

E T x(l,d)= L·E elec+L·?fs·d2if d

L·E elec+L·?mp·d4if d≥d0 where E elec is the energy dissipated per bit to run the transmitter or the receiver circuit,?fs and?mp depend on the transmitter ampli?er model we use,and d is the distance between the sender and the

010*******

400500600

7008009001000

2530

Optimal number of constructed clusters (k opt ) per round

O p t i m a l n u m b e r o f c l u s t e r s

Figure 2:(top)Optimal number of clusters;and (bottom)Optimal

probability of a node to become a cluster head,as a function of number of nodes in a 100m ×100m ?eld where the sink is located in the center.

receiver.By equating the two expressions at d =d 0,we have d 0= ?fs ?mp

.To receive an L ?bit message the radio expends E Rx =L ·E elec .

Assume an area A =M ×M square meters,and n the number of nodes that are uniformly distributed over that area.For simplicity,assume the sink is located in the center of the ?eld,and that the maximum distance of any node to the sink is ≤d 0.Thus,the energy dissipated in the cluster head node during a round is given by the following formula:

E CH =L ·E elec

n ?1 +L ·E DA n +L ·E elec +L ·?fs d 2toBS where k is the number of clusters,E DA is the processing (data aggregation)cost of a bit per signal,and d toBS is the distance be-tween the cluster head and the sink.The energy used in a non-cluster head node is equal to:

E nonCH =L ·E elec +L ·?fs ·d 2toCH

where d toCH is the distance between a cluster member and its cluster head.Assuming that the nodes are uniformly distributed,it can be shown that:

E [d 2toCH ]=

(x 2+y 2

)ρ(x,y )dxdy =

M 2where ρ(x,y )is the node distribution.

The energy dissipated in a cluster per round is the following:E cluster ≈E CH +n k E nonCH

The total energy dissipated in the network is equal to:E tot =L ·

2nE elec +nE DA +?fs (k ·

d 2toBS

M 2

)

By differentiating E tot with respect to k and equating to zero,the optimal number of constructed clusters can be found:2

k opt = n M toBS = n 2

(2)

because the average distance from a cluster head to the sink is

given by [3]:

E [d toBS ]=

x 2+y 21A dA =0.765M

2The optimal probability of a node to become a cluster head,p opt ,can be computed as follows:

p opt =

k opt

(3)

Figure 2shows the values of k opt and p opt as a function of the number of nodes in a 100m ×100m ?eld where the sink is lo-cated in the center.The optimal construction of clusters (which is equivalent to the setting of the optimal probability for a node to be-come a cluster head)is very important.In [6],the authors showed that if the clusters are not constructed in an optimal way,the total consumed energy of the sensor network per round is increased ex-ponentially either when the number of clusters that are created is greater or especially when the number of the constructed clusters is less than the optimal number of clusters.Our simulation results con?rm this observation in our case where the sink is located in the center of the sensor ?eld.

3.PERFORMANCE MEASURES

We de?ne here the measures we use in this paper to evaluate the performance of clustering protocols.

?Stability Period:is the time interval from the start of network operation until the death of the ?rst sensor node.We also refer to this period as “stable region.”?Instability Period:is the time interval from the death of the ?rst node until the death of the last sensor node.We also refer to this period as “unstable region.”?Network lifetime:is the time interval from the start of oper-ation (of the sensor network)until the death of the last alive node.?Number of cluster heads per round:This instantaneous mea-sure re?ects the number of nodes which would send directly to the sink information aggregated from their cluster mem-bers.?Number of alive (total,advanced and normal)nodes per round:This instantaneous measure re?ects the total number of nodes and that of each type that have not yet expended all of their energy.2

It is interesting to notice that the optimal number of clusters is independent of the dimensions of the ?eld and only depends on the number of nodes n .

Figure3:(top)A wireless sensor network;(middle)An instance of the network where all the nodes are alive;(bottom)An instance of the network where some nodes are dead.

?Throughput:We measure the total rate of data sent over the network,the rate of data sent from cluster heads to the sink as well as the rate of data sent from the nodes to their cluster heads.

Clearly,the larger the stable region and the smaller the unstable region are,the better the reliability of the clustering process of the sensor network is.On the other hand,there is a tradeoff between reliability and the lifetime of the system.Until the death of the last node we can still have some feedback about the sensor?eld even though this feedback may not reliable.The unreliability of the feedback stems from the fact that there is no guarantee that there is at least one cluster head per round during the last rounds of the operation.In our model,the absence of a cluster head prevents any reporting about that cluster to the sink.The throughput measure captures the rate of such data reporting to the sink.

4.HETEROGENEOUS-OBLIVIOUS

PROTOCOLS

The original version of LEACH does not take into consideration the heterogeneity of nodes in terms of their initial energy,and as a result the consumption of energy resources of the sensor network is not optimized.The reason is that LEACH depends only on the spatial density of the sensor network.

Using LEACH in the presence of heterogeneity,and assuming both normal and advanced nodes are uniformly distributed in space, we expect that the?rst node dies on average in a round that is close to the round where the?rst node dies in the homogeneous case wherein each node is equipped with the same energy as that of a normal node in the heterogeneous case.Furthermore,we ex-pect the?rst dead node to be a normal node.We also expect that in the following rounds the probability of a normal node to die is greater than the probability of an advanced node to die.During the last rounds only advanced nodes are alive.Our expectations are con?rmed by simulation results in Section6.We next demon-strate how such heterogeneous-oblivious clustering protocol fails to maintain the stability of the system,especially when nodes are het-erogeneous.This motivates our proposed SEP protocol presented in Section5.

4.1Instability of Heterogeneous-oblivious

Protocols

In this section we discuss the instability of heterogeneous-oblivious protocols,such as LEACH,once some nodes die.In this case,the process of optimal construction of clusters fails since the spatial density deviates from the assumed uniform distribution of nodes over the sensor?eld.

Let us assume a heterogeneous(m=0.2,α=1)sensor net-work in a100m×100m sensor?eld,as shown in Figure3(top).For this setting we can compute from Equation(2)the optimal number of clusters per round,k opt=10.We denote with?a normal node, with+an advanced node,with·a dead node,with?a cluster head and with×the sink.As long as all the nodes are alive,the nodes that are included in the same V oronoi cell will report to the cluster head of this cell;see Figure3(middle).

At some point the?rst node dies;see Figure3(bottom).Af-ter that point the population of sensors decreases as nodes die ran-domly.The population reduction introduces instability in the sen-sor network and the cluster head election process becomes unreli-able.This is because the value of p opt is optimal only when the population of the network is constant and equal to the initial popu-lation(n).When the population of the nodes starts decreasing the number of elected cluster heads per round is very unstable(lower than intended)and as a result there is no guarantee that a constant number of cluster heads(equal to n×p opt)will be elected per round per epoch.Moreover there are less alive nodes so the sam-pling(sensing)of the?eld is over less nodes than intended to be. The only guarantee is that there will be at least one cluster head per epoch(cf.Equation1).As a result at least in one round per epoch all alive nodes will report to the sink.The impact and qual-

ity of these reports highly depends on the application.For some applications even this minimal reporting is a valuable feedback,for others it is not.Clearly minimal reporting translates to signi?cant under-utilization of the resources and the bandwidth of the applica-tion.

LEACH guarantees that in the homogeneous case the unstable region will be short.After the death of the?rst node,all the remain-ing nodes are expected to die on average within a small number of rounds as a consequence of the uniformly remaining energy due to the well distributed energy consumption.Even when the system operates in the unstable region,if the spatial density of the sen-sor network is large,the probability that a large number of nodes be elected as cluster heads is signi?cant for a signi?cant part of the unstable region(as long as the population of the nodes has not been decreased signi?cantly).In this case,even though our system is unstable in this region,we still have a relatively reliable cluster-ing(sensing)process.The same can be noticed even if the spatial density is low but the p opt is large.On the other hand LEACH in the presence of node heterogeneity yields a large unstable region. The reason is that all advanced nodes are equipped with almost the same energy but,the cluster head election process is unstable and as a result most of the time these nodes are idle,as there is no cluster head to transmit.

In the next section,we introduce our new heterogeneous-aware SEP protocol whose goal is to increase the stable region and as a result decrease the unstable region and improve the quality of the feedback of wireless clustered sensor networks,in the presence of heterogeneous nodes.

5.OUR SEP PROTOCOL

In this section we describe SEP,which improves the stable re-gion of the clustering hierarchy process using the characteristic pa-rameters of heterogeneity,namely the fraction of advanced nodes (m)and the additional energy factor between advanced and normal nodes(α).

In order to prolong the stable region,SEP attempts to maintain the constraint of well balanced energy consumption.Intuitively, advanced nodes have to become cluster heads more often than the normal nodes,which is equivalent to a fairness constraint on en-ergy consumption.Note that the new heterogeneous setting(with advanced and normal nodes)has no effect on the spatial density of the network so the apriori setting of p opt,from Equation(3), does not change.On the other hand,the total energy of the system changes.Suppose that E o is the initial energy of each normal sen-sor.The energy of each advanced node will be E o·(1+α).The total energy of the new heterogeneous setting is equal to:

n·(1?m)·E o+n·m·E o·(1+α)=n·E o·(1+α·m) So,the total energy of the system is increased by1+α·m times. The?rst improvement to the existing LEACH is to increase the epoch of the sensor network in proportion to the energy increment. In order to optimize the stable region of the system,the new epoch must become equal to1

p opt

·(1+α·m)because the system has α·m times more energy and virtuallyα·m more nodes(with the same energy as the normal nodes).

We can now increase the stable region of the sensor network by 1+α·m times,if(i)each normal node becomes a cluster head once every1

p opt

·(1+α·m)rounds per epoch;(ii)each advanced node

becomes a cluster head exactly1+αtimes every1

opt ·(1+α·m)

rounds per epoch;and(iii)the average number of cluster heads per round per epoch is equal to n×p opt(the spatial density does not change).Constraint(ii)is very strict—If at the end of each epoch

Figure4:Performance of na¨?ve solution.

the number of times that an advanced sensor has become a cluster head is not equal to1+αthen the energy is not well distributed and the average number of cluster heads per round per epoch will be less than n×p opt.This problem can be reduced to a problem of optimal threshold T(s)setting(cf.Equation1),with the constraint that each node has to become a cluster head as many times as its initial energy divided by the energy of a normal node.

5.1The Problem of Maintaining Well

Distributed Energy Consumption

Constraints in the Stable Period

If the same threshold is set for both normal and advanced nodes with the difference that each normal node∈G becomes a cluster head once every1

p opt

·(1+α·m)rounds per epoch,and each advanced node∈G becomes a cluster head1+αtimes every 1

opt

·(1+α·m)rounds per epoch,then there is no guarantee that the number of cluster heads per round per epoch will be n×p opt. The reason is that there is a signi?cant number of cases where this number can not be maintained per round per epoch with probability 1.A worst-case scenario could be the following.Suppose that all normal nodes become cluster heads once within the?rst1

opt

·(1?m)rounds of the epoch.In order to maintain the well distributed energy consumption constraint,all the remaining nodes,which are advanced nodes,have to become cluster heads with probability1 for the next1

p opt

·m·(1+α)rounds of the epoch.But the threshold T(s)is increasing with the number of rounds within each epoch and becomes equal to1only in the last round(all the remaining nodes in the last round become cluster head with probability1). So the above constraint is not satis?ed.Figure4shows that the performance of this na¨?ve solution is very close to that of LEACH. In the next subsection,we introduce SEP where the extra energy of advanced nodes is forced to be expended within subepochs of the original epoch.

5.2Guaranteed Well Distributed Energy

Consumption Constraints in the Stable

Period

In this section we propose a solution,we call SEP(Stable Elec-tion Protocol),which is based on the initial energy of the nodes.

This solution is more applicable compared to any solution which assumes that each node knows the total energy of the network in order to adapt its election probability to become a cluster head ac-cording to its remaining energy [5].Our approach is to assign a weight to the optimal probability p opt .This weight must be equal to the initial energy of each node divided by the initial energy of the normal node.Let us de?ne as p nrm the weighted election proba-bility for normal nodes and p adv the weighted election probability for the advanced nodes.

Virtually there are n ×(1+α·m )nodes with energy equal to the initial energy of a normal node.In order to maintain the minimum energy consumption in each round within an epoch,the average number of cluster heads per round per epoch must be constant and equal to n ×p opt .In the heterogeneous scenario the average number of cluster heads per round per epoch is equal to n ·(1+α·m )×p nrm (because each virtual node has the initial energy of a normal node).The weighed probabilities for normal and advanced nodes are,respectively:

p nrm =

p opt 1+α·m

p adv =

p opt

1+α·m

×(1+α)

In Equation (1),we replace p opt by the weighted probabilities to obtain the threshold that is used to elect the cluster head in each round.We de?ne as T (s nrm )the threshold for normal nodes and T (s adv )the threshold for advanced nodes.Thus,for normal nodes,we have:

T (s nrm )= p nrm

1?p nrm ·(r mod 1p nrm )

if s nrm ∈G ′

0otherwise (4)

where r is the current round,G ′is the set of nodes that have

not become cluster heads within the last 1

nrm

rounds of the epoch,and T (s nrm )is the threshold applied to a population of n ·(1?m )(normal)nodes.This guarantees that each normal node will

become a cluster head exactly once every 1

p opt ·(1+α·m )rounds per epoch,and that the average number of cluster heads per round per epoch is equal to n ·(1?m )×p nrm .Similarly,for advanced nodes,we have:

T (s adv )= p adv

1?p adv ·(r mod 1p adv

)

if s adv ∈G ′′

0otherwise (5)where G ′′is the set of nodes that have not become cluster heads within the last 1

p adv rounds of the epoch,and T (s adv )is the thresh-old applied to a population of n ·m (advanced)nodes.This guar-antees that each advanced node will become a cluster head exactly

once every 1p opt ·1+α·m

1+α

rounds.Let us de?ne this period as sub-epoch .It is clear that each epoch (let us refer to this epoch as “heterogeneous epoch”in our heterogeneous setting)has 1+αsub-epochs and as a result,each advanced node becomes a cluster head exactly 1+αtimes within a heterogeneous epoch.The av-erage number of cluster heads per round per heterogeneous epoch (and sub-epoch)is equal to n ·m ×p adv .

The average number of cluster heads per round per heteroge-neous epoch is equal to the average number of cluster heads that are normal nodes per round per heterogeneous epoch plus the aver-age number of cluster heads that are advanced nodes per round per sub-epoch.This average number is given by:

n ·(1?m )×p nrm +n ·m ×p adv =n ×p opt

x=0x=1x=2x=3x=4x=5x=7x=6x=9

x=8x’=0 x’=1 sub-epoch

epoch

heterogeneous epoch

sub-epoch sub-epoch sub-epoch x’=13x’=15

x’=14x’=10x’=12x’=9x’=11x’=7x’=8x’=6x’=5x’=4x’=3x’=2Figure 5:A numerical example for a heterogeneous network with

parameters m =0.2and α=3and p opt =0.1.We de?ne as x =r mod 1opt

and as x ′=r mod 1nrm ,where r is the cur-rent round.

which is the desired number of cluster heads per round per epoch.We next discuss the implementation of our SEP protocol.

5.3SEP Deployment

As mentioned in Section 1,the heterogeneity in the energy of nodes could result from normal network operation.For example,nodes could,over time,expend different amounts of energy due to the radio communication characteristics,random events such as short-term link failures or morphological characteristics of the ?eld (e.g.uneven terrain).To deal with such heterogeneity,our SEP pro-tocol could be triggered whenever a certain energy threshold is ex-ceeded at one or more nodes.Non-cluster heads could periodically attach their remaining energy to the messages they sent during the handshaking process with their cluster heads,and the cluster heads could send this information to the sink.The sink can check the heterogeneity in the ?eld by examining whether one or a certain number of nodes reach this energy threshold.If so,then the sink could broadcast to cluster heads in that round the values for p nrm and p adv ,in turn cluster heads unicast these values to nodes in their clusters according to the energy each one has attached earlier dur-ing the handshaking process.

If some of the nodes already in use have not been programmed with this capability,a reliable transport protocol,such as the one proposed in [10],could be used to program such sensors.Eval-uating the overhead of such SEP deployment is a subject of our on-going work.

5.4Numerical Example

Assume that 20%of the nodes are advanced nodes (m =0.2)and equipped with 300%more energy that other (normal)nodes (α=3).Consider a population of a sensor network in a 100m ×100m ?eld of 100nodes.The p opt for this setting is approximately equal to 0.104325(cf.Figure 2).For simplicity let us set p opt =0.1.This means that on average,10nodes must become cluster heads per round.

If we consider a homogeneous scenario where each node has initial energy equal to the energy of a normal node,then the epoch

would be equal to 1

opt

=10rounds.In our heterogeneous case,the extended heterogeneous epoch is equal to

1+α·m p opt

1p nrm

16rounds,and each sub-epoch is equal to 1p opt

·1+α·m

1+α=4rounds,

as illustrated in Figure 5.On average,n ·(1?m )×p nrm =5normal nodes become cluster heads per round and all of them will become cluster heads exactly once within 16rounds (one heteroge-neous epoch).Furthermore,on average,n ·m ×p adv =5advanced nodes become cluster head per round.The total number of sensors that become cluster heads (both normal and advanced)is equal to 10,which is the desired number.Moreover each advanced sensor becomes a cluster head exactly once every sub-epoch and becomes

n u m b e r o f a l i v e n o d e s

Figure 6:Number of alive nodes using LEACH in the presence of

heterogeneity:(top)m =0.1and α=2,and (bottom)m =0.2and α=1.

(1+α)times a cluster head within a heterogeneous epoch,i.e.each advanced node becomes a cluster head 4times within a heteroge-neous epoch.

Operation

Energy Dissipated Transmitter/Receiver Electronics

E elec =50nJ/bit Data Aggregation E DA =5nJ/bit/signal Transmit Ampli?er if d max toBS ≤d 0?fs =10pJ/bit/m 2Transmit Ampli?er if d max toBS ≥d 0

?mp =0.0013pJ/bit/m 4

Table 1:Radio characteristics used in our simulations.

6.SIMULATION RESULTS

We simulate a clustered wireless sensor network in a ?eld with dimensions 100m ×100m .The population of the sensors is equal to n =100and the nodes,both normal and advanced,are ran-domly (uniformly)distributed over the ?eld.This means that the horizontal and vertical coordinates of each sensor are randomly se-lected between 0and the maximum value of the dimension.The

sink is in the center and the maximum distance of any node from the sink is approximately 70m (the setting of Figure 3).This set-ting is realistic for most of outdoor applications.The initial energy of a normal node has been set to E 0=0.5J (equal to one AA battery)—Although this value is arbitrary for the purpose of this study,this does not affect the behavior of our method.The radio characteristics used in our simulations are summarized in Table 1.The size of the message that nodes send to their cluster heads as well as the size of the (aggregate)message that a cluster head sends to the sink is set to 4000bits.

In the next subsections we simulate the heterogeneous-oblivious LEACH and our SEP protocol,in the presence of heterogeneity in the initial energy of nodes.We evaluate the behavior of both proto-cols in terms of the performance measures de?ned in Section 3.We also examine the sensitivity of SEP to the degree of heterogeneity in the network.We ?rst summarize our general observations:?In a wireless sensor network of heterogeneous nodes,LEACH goes to unstable operation sooner as it is very sensitive to such heterogeneity.?Our SEP protocol successfully extends the stable region by being aware of heterogeneity through assigning probabilities of cluster-head election weighted by the relative initial en-ergy of nodes.?Due to extended stability,the throughput of SEP is also higher than that of current (heterogeneous-oblivious)clustering pro-tocols.?The performance of SEP is observed to be close to that of an ideal upper bound obtained by distributing the additional energy of advanced nodes uniformly over all nodes in the sensor ?eld.?SEP is more resilient than LEACH in judiciously consum-ing the extra energy of advanced nodes—SEP yields longer stability region for higher values of extra energy.

6.1Results for LEACH

The results of our LEACH simulations are shown in Figure 6(a)for m =0.1and α=2.We observe that LEACH takes some advantage of the presence of heterogeneity (advanced nodes),as the ?rst node dies after a signi?cantly higher number of rounds (i.e.longer stability period)compared to the homogeneous case (m =α=0).The lifetime of the network is increased,but as we will show later this does not mean that the nodes transmit (i.e.the throughput is low).The reason is that after the death of a signi?cant number of nodes,the cluster head election process becomes unsta-ble and as a result less nodes become cluster heads.Even worse,during the last rounds,there are only few rounds where more than one cluster head is elected.3

We repeat the same experiment,but now the heterogeneity pa-rameters are set to m =0.2and α=1,however m ×αremains constant.Our simulation results are shown in Figure 6(bottom).Although the length of the stability region (until the ?rst node dies)is pretty stable,LEACH takes more advantage of the presence of heterogeneity manifested in a higher number of advanced nodes.In Figure 7,a detailed view of the behavior of LEACH is il-lustrated,for different distributions of heterogeneity.In Figure 3

For both LEACH and SEP,the length of the stable region obtained from independent simulation runs (i.e.starting from different ran-dom number seeds)is pretty stable for the same values of m and α.

Figure7:LEACH behavior in the presence of heterogeneity with m=0.2andα=3:(a)Alive nodes per round;(b)Average number of cluster heads per round per epoch;(c)Normal nodes per round;(d)Advanced nodes per round

7(a),the number of alive nodes is shown for the scenarios(m= 0.2,α=1)and(m=0.2,α=3).LEACH fails to take full advantage of the heterogeneity(extra energy)as in both scenarios, the?rst node dies almost at the same round.Moreover,the nor-mal nodes die in both cases very fast(Figure7(c))and as a result the sensing?eld becomes sparse very fast.On the other hand,ad-vanced nodes die in a very slow fashion(Figure7(d)),because they are not elected very often as cluster heads after the death of the nor-mal nodes(and thus they do not transmit most of the time)—this is because the election process for cluster heads has become unstable and the number of cluster heads elected are less than the optimal number.Furthermore,as shown in Figure7(b),when a signi?cant number of normal nodes are dead the average number of cluster heads per round per epoch is less than one.This means that in most of the rounds there is no cluster head,so in our model the remaining nodes can not report their values to the sink.

6.2Results for SEP

In this subsection we compare the performance of our SEP proto-col to1)LEACH in the same heterogeneous setting,and2)LEACH where the the extra initial energy of advanced nodes is uniformly distributed over all nodes in the sensor?eld.This latter setting turns out to provide the highest throughput during the unstable region—we henceforth refer to it as FAIR(for the“fair”distribution of extra energy over existing nodes).

Figure8(top)shows results for the case of m=0.2andα=1. It is obvious that the stable region of SEP is extended compared of that of LEACH(by8%),even though the difference is not very large.Moreover,the unstable region of SEP is shorter than that of LEACH.What is more important to notice is that the stable region of SEP is even greater than FAIR.Furthermore the unstable region of SEP is slightly larger than that of FAIR,and the number of alive nodes per round in SEP is very close to that of FAIR.

Figure8(bottom)shows results for the case of m=0.2and α=3.Now SEP takes full advantage of heterogeneity(extra energy of advanced nodes)—the stable region is increased signif-icantly(by26%)in comparison with that of LEACH.Again the stable region of SEP is greater than that of FAIR.The unstable re-gion of SEP is shorter than that of LEACH,and the number of alive nodes under SEP is close to that of FAIR.This is because the advanced nodes follow the dying process of normal nodes,as the weighted probability of electing cluster heads causes energy of each node to be consumed in proportion to the node’s initial energy.

We study here the sensitivity of our SEP protocol,in terms of the length of the stability period,by varying m andα.Figure10(top) shows the length of the stability region versus m×α.We found that the performance does not depend on the individual values of m and αbut rather on their product,which represents the total amount of Figure9:Throughput comparison between LEACH and SEP in the presence of heterogeneity with m=0.2andα=3:(top)Cluster heads to sink;(middle)Nodes to their cluster heads;and(bottom)Total for the whole network.

extra initial energy brought by advanced nodes.Figure10(middle)

shows the percentage gain in the length of the stability region over the case of m=0andα=0,i.e.without the added energy of advanced nodes.Figure10(bottom)shows the percentage gain in the length of the stability region of one protocol over another.

We observe that,as expected,the stability period under FAIR in-creases linearly with m×α.On the other hand,the stability period under SEP and LEACH increases faster but then more slowly be-yond a“knee”point.Moreover,as far as the ef?cient use of extra energy,the percentage gain in the stability period is maximized un-der SEP for most values of m×α.In all cases SEP outperforms LEACH.

Interestingly,both SEP and LEACH outperforms FAIR for small amount of heterogeneity(or a small number of advanced nodes)—SEP outperforms FAIR by up to18%(when m×α=0.2),and LEACH outperforms FAIR by up to11%(when m×α=0.2).This is because these advanced nodes are uniformly distributed over the sensor?eld,and when they elect themselves as cluster heads,their “extra”energy is consumed more judiciously than if some of this extra energy was distributed to all nodes(as in FAIR)which are possibly farther away from the sink.This gain over FAIR eventu-ally vanishes when it becomes more bene?cial to distribute some extra energy to the fewer normal nodes.

We also notice that the gain of SEP over LEACH increases as m×αincreases—SEP outperforms LEACH by up to33%when m×α=0.9.The gain of LEACH over FAIR drops much faster than that of SEP after the“knee”point.This indicates that the management of the extra energy of advanced nodes can become dif?cult,more so for LEACH than our SEP protocol.

7.RELATED WORK

In addition to related work cited throughout the paper,in this section we review speci?c prior studies that dealt with the hetero-geneity in energy of sensor nodes.

The?rst work that questioned the behavior of clustering proto-cols in the presence of heterogeneity in clustered wireless sensor networks was[5].In this work Heinzelman analyzed a method to elect cluster heads according to the energy left in each node.The drawback of this method is that this decision was made per round and assumed that the total energy left in the network was known. The complexity and the assumption of global knowledge of the en-ergy left for the whole network makes this method dif?cult to im-plement.Even a centralized approach of this method would be very complicated and very slow,as the feedback should be reliably de-livered to each sensor in every round.

In[4],Duarte-Melo and Liu examined the performance and en-ergy consumption of wireless sensor networks,in a?eld where there are two types of sensors.They consider nodes that are fewer but more powerful that belong to an overlay.All the other nodes have to report to these overlay nodes,and the overlay nodes aggre-gate the data and send it to the sink.The drawback of this method is that there is no dynamic election of the cluster heads among the two type of nodes,and as a result nodes that are far away from the powerful nodes will die?rst.The authors estimate the optimal percentage of powerful nodes in the?eld,but this result is very dif?cult to use when heterogeneity is a result of operation of the sensor network and not a choice of optimal setting.

In[8],Mhatre and Rosenberg presented a cost based comparative study of homogeneous and heterogeneous clustered wireless sensor networks.They proposed a method to estimate the optimal distri-bution among different types of sensors,but again this result is hard to use if the heterogeneity is due to the operation of the network. They also studied the case of multi-hop routing within each cluster

Figure10:Sensitivity of LEACH,SEP,and FAIR to degree of hetero-geneity.

(called M-LEACH).Again the drawback of the method is that only powerful nodes can become cluster heads(even though not all of the powerful nodes are used in each round),and that M-LEACH is valid under many assumptions and only when the population of the nodes is very large.

8.CONCLUSIONS AND FUTURE WORK We proposed SEP(Stable Election Protocol)so every sensor node in a heterogeneous two-level hierarchical network indepen-dently elects itself as a cluster head based on its initial energy rela-tive to that of other nodes.Unlike[5],we do not require any global knowledge of energy at every election round.Unlike[4,8],SEP is dynamic in that we do not assume any prior distribution of the dif-ferent levels of energy in the sensor nodes.Furthermore,our anal-ysis of SEP is not only asymptotic,i.e.the analysis applies equally well to small-sized networks.

We are currently extending SEP to deal with clustered sensor networks with more than two levels of hierarchy and more than two types of nodes.We are also implementing SEP in Berke-ley/Crossbow motes and examining deployment issues including dynamic updates of weighted election probabilities based on cur-rent heterogeneity conditions.

SEP code and results are publicly available at https://www.doczj.com/doc/f912271164.html,/sep.

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新生儿转运制度及实施细则

新生儿转运制度及实施细则一、为适应新形式下对危重新生儿转运要求，提高危重新生儿转运安全性及抢救成功率，提高我院新生儿专业辐射力及影响力，参考XX 儿童医院120急救转运管理制度，结合新生儿转运特点，制定新生儿内科/NICU 新生儿转运制度。二、成立新生儿病区“新生儿转运”管理小组组长：副组长：成员：医疗组：护理组：三、出诊医生接到转运电话后，详细询问患儿一般情况（姓名、性别、日龄、孕周）、转诊原因及目前患儿病情情况，并评估、解释、记录，告知对方转运风险及相关费用。四、通知护士、司机，启动转运程序，药、物、设备检查齐全；根据病情确定出诊时应配备的特殊抢救器械及药物，3分钟内出发。120转运电话要求保持24小时畅通，保障与对方电话联系；五、到达目的医院首先听取当地医生病情介绍；检查患儿情况，再次评估患儿病情，是否适合转运；将患儿病情及评估结果告知家长，说明风险，签订转运同意书，1-2名家长随车。六、不适合转运的患儿向家人仔细解释，家人理解后签署拒绝转运；特殊病人，如转运风险较大，或与当地医院有潜在医疗纠纷者，应及时上报李振光科主任或院总值班。

七、转运途中根据病情积极采取相应治疗及护理措施；转入NICU患儿需提前半小时电话通知NICU病区值班医护人员，告知患儿病情，准备抢救物品及器材；如需外科会诊，提前联系相应科室做好会诊工作；如需辅助科室检查，提前与相应辅助科室电话联系。八、抵达我院后，转运医护人员护送患儿直接入NICU，向接诊医师交代病情，认真填写相关医疗文件，并签字确认。九、转运护士带领患儿家人办理相关入院手续；请家长保持电话畅通，如有特殊情况会及时联系。十、吴宏伟副主任医师、郝祥梅护士长作为新生儿转运直接责任人，执行日常转运运转及培训工作，每季度对院前急救人员进行一次院前急救知识培训并有相应的考核记录，院前急救质量标准为100分，合格为90分，合格率要求为100%；十一、120车由专人（王妍妍）负责监管，每两周对120车进行专项检查1次，护士长每月对120车跟踪检查1次。十二、120车载仪器设备、物品、药品严格执行“五定”制度（定人保管，定时核对，定点放置，定量配置，定期消毒），每天由120 班护士负责，保证设备功能良好、抢救药品齐全。交接班并记录，发现问题及时解决。十三、王妍妍护师负责每季度新生儿转运总结，总结转运过程中存在的问题，及时发现潜在风险，组织科内讨论并改进，有相应讨论记录。十四、以上制度及流程由科务会组织讨论制定，并上报院医务科。

危重新生儿转运的护理体会

危重新生儿转运的护理体会摘要本文对85例危重新生儿院外转运过程中的相关护理进行总结，主要对转运前设备及人员的准备、转运中病情的观察及护理措施、转运后患儿交接及设备维护。 Abstract In this paper, we summarized relevant care experience about 85 cases of hospital transport of critically ill newborns,including preparation of equipment and manpower allocation before the transit,observation and nursing invention of critical patients during the transit,transference of critical patients and equipment maintenance after the transit. KEYWORD newborn;critically ill newborns;transit;nursing invention 关键词新生儿：危重患儿；转运；护理新生儿转运系统( neonatal emergency transport system, NETS)于1950年在美国形成，是一项由接收医院主动把“流动的新生儿重症监护中心(NICU)”送到危重患儿身边的双程转运系统, 它以一个三级医院为中心, 向周围辐射, 集转运、通讯联络和培训为一个整体的特殊医疗系统, 主要通过有计划、有组织地对基层医院中的高危新生儿进行就地抢救, 待病情稳定后再转送NICU, 使危重患儿得到更好地诊疗与护理, 从而降低新生儿病死率与致残率[1]。我院于2010年7月新生儿科建立起覆盖津冀两地的危重新生儿院前急救与转运系统，有先进专业的转运设备和规范化的转运流程，在转运过程中通

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门组织，建立由上级专家参加的评审委员会，采用材料审核和现场评估的方式确认。第五条危重新生儿救治中心的设置应当符合区域医疗卫生服务体系规划，遵循择优确定、科学布局、分级诊疗的原则。（一）地方各级卫生计生行政部门应当根据医疗机构设置规划和新生儿诊疗需求，对区域内危重新生儿救治中心的数量和布局进行统筹规划。（二）医疗机构可以根据区域医疗服务需求、区域卫生规划和医疗机构设置规划，结合自身功能定位确定危重新生儿救治中心服务能力的层级目标。（三）原则上所有的省（区、市）、市（地、州）、县（市、区）行政区域应当至少设立1个服务能力不低于相应层级的危重新生儿救治中心。第六条各级行政区域应依托危重新生儿救治中心建立健全危重新生儿救治协作网，参照新生儿转运工作指南开展转运工作。所有开展危重新生儿医疗服务的机构，超出技术能力范围或床位满员时，应当及时将患儿转运至适宜的危重新生儿救治中心，以保证区域内每个新生儿均能及时获得适当的医疗与护理服务。第七条危重新生儿救治中心应当系统开展区域内相关专业人员的技术培训和继续教育，积极开展科研工作，组织或

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6、出生体重W800克。三、转运前得处理及判断 1、选择一个就近、技术力量雄厚得上级医院，及时通知上级医院进行转运。 2、转运前应积极治疗、密切监护与稳定患儿得体内环境，不能认为患儿马上要被转运而不闻不问。 3、转运前应对患儿得下列状态作出判断 (1)心血管功能:有无心力衰竭，什么原因引起？如有心衰则限制入液量，选用利尿剂及地高辛。皮肤灌注不好者，分析原因：失血？严重感染？心功能不全？酸碱紊乱？采取相应得措施，用多巴胺、碳酸氢钠或机械呼吸等措施。若有严重心律失常，予相应药物治疗。 (2)肺部情况:呼吸功能如何(结合体格检查及血气分析)，需否气管插管？如存在缺氧，青紫应调整FiO2,做持续气道正压(CPAP)呼吸，若已做机械通气则调整呼吸器参数，并应了解有无气胸存在，作相应处理。 (3)7解体温及环境温度。 (4)T解生化/代谢状态:如低血糖、酸中毒、低钠血症。低血糖, 应迅速纠正，酸中毒者纠正至pHM7、2低钠血症应逐渐纠正。 (5)有无重度细菌感染:根据病史、体检、血白细胞计数及等检查分析细菌感染得可能性，若考虑有细菌感染即应抽血培养，并开始抗生素治疗。 (6)7解中枢神经系统情况:就是否过度兴奋或抑制，有无颅内出血？如有惊厥注射苯巴比妥。 (7)有无外科疾患。四、制定规范转诊同意书及转运情况介绍 1、转诊前要填写转诊记录单：包括病史、辅助检查结果与治疗进行详细登记,有助于减少转运风险及后续处理。 2、向家长解释患儿病情、转院得原因、预后得估计与转运风险等问题，取得家长得理解与合作就是成功转运得基础。

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Flow chart of regional neonatal transport network (1)较高等级的RNTN可包含较其低等级的RNTN。后者可依次作为前者的分系统或子系统，既参与整个系统的运作，又组织各自局部系统的运作。NCC应遵照其层级所定义的医护服务条件和能力接收新生儿，一般病情患儿提倡按NCC等级逐级实施转运，特殊病情患儿可根据需要越级实施转运[6,7]。 (2)确定RNTN的范围应以"适宜、就近"为原则，在行政区划的基础上兼顾地方就医习惯和地理距离。有条件的情况下，同一区域可同时有多个RNTN提供服务；不要求RNTN中NCC与转出医疗机构之间是专属关系，可允许与其他RNTN之间有交互联系[1]。 (3)RNTN所服务区域的大小受其层级限制，结合地理形态、人口密度、气候条件、区域经济、医保支付和可提供适当服务的NCC数量等综合考虑。采用救护车转运，RNTN服务半径一般以200～400 km为宜，除确认患儿病情许可且必须转运外，超出此范围应选用其他更高速的交通工具。 (4)RNTN采用"综合、主动、全程、立体型"技术服务模式为宜[3,4,5,6,7,8]。业务内容应为涵盖高危儿转运救治、人员培训和科学研究的全方位服务，转运形式以NCC接回患儿的主动转运为主，转运的服务范围应包括产房待产、新生儿转运和宫内转运，转运途径应逐步拓展为陆路、航空和水路结合的立体型交通网。 2 NT的队伍建设 2.1 NT机构

全版新生儿转运工作指南.doc

新生儿转运工作指南新生儿转运(neonatal transport，NT)是危重新生儿救治中心(newborn care center，NCC)的重要工作内容之一，目的是安全地将高危新生儿转运到NCC的新生儿重症监护病房(neonatal intensive care unit，NICU)进行救治，充分发挥优质卫生资源的作用。然而，转运过程中可能存在患儿病情变化和死亡的风险，要实现安全、快速地转运，必须规范和优化NT工作，以达到降低新生儿病死率的目的。因此，结合近几年转运工作的新进展新经验，本指南对2013年版《中国新生儿转运指南》进行更新和完善，以供新生儿医师参考。 1建立区域性新生儿转运网络(regional neonatal transport network，RNTN) RNTN是由区域内不同等级的NCC和相关医疗保健机构组成，以NCC为中心，集转运、救治、研究和培训为一体的特殊医疗服务系统。网络关系见图。

(1)较高等级的RNTN可包含较其低等级的RNTN。后者可依次作为前者的分系统或子系统，既参与整个系统的运作，又组织各自局部系统的运作。NCC应遵照其层级所定义的医护服务条件和能力接收新生儿，一般病情患儿提倡按NCC等级逐级实施转运，特殊病情患儿可根据需要越级实施转运。 (2)确定RNTN的范围应以"适宜、就近"为原则，在行政区划的基础上兼顾地方就医习惯和地理距离。有条件的情况下，同一区域可同时有多个RNTN提供服务；不要求RNTN中NCC与转出医疗机构之间是专属关系，可允许与其他RNTN之间有交互联系。 (3)RNTN所服务区域的大小受其层级限制，结合地理形态、人口密度、气候条件、区域经济、医保支付和可提供适当服务的NCC数量等综合考虑。采用救护车转运，RNTN服务半径一般以200～400 km为宜，除确认患儿病情许可且必须转运外，超出此范围应选用其他更高速的交通工具。 (4)RNTN采用"综合、主动、全程、立体型"技术服务模式为宜。业务内容应为涵盖高危儿转运救治、人员培训和科学研究的全方位服务，转运形式以NCC接回患儿的主动转运为主，转运的服务范围应包括产房待产、新生儿转运和宫内转运，转运途径应逐步拓展为陆路、航空和水路结合的立体型交通网。 2 NT的队伍建设 2.1 NT机构 NCC设转运服务台，有条件的应设立转运服务处。其职能主要是转运组织管理和质量控制。 (1)预备管理：转运车辆、设备和药品等由转运处统一管理，应每天检查物品完备完好情况。车辆设备应做好定期保养，发现故障隐患应及时维修，使其时刻处于良好备用状态。 (2)过程管理：实行24 h值班制，及时合理调度车辆和人员。实行转运人员亲笔签到制度，以督导及时出发。与转运任务中相关人员保持随时联系以准确掌握动态。

(完整版)新生儿指南汇编详解

目录新生儿黄疸干预推荐方案 (1) 新生儿高胆红素血症的防治 (3) 美国儿科学会最新新生儿黄疸诊疗指南......................................................... 6早产儿管理指南.......................................................................................9中国新生儿营养支持临床应用指南.............................................................. 13新生儿静脉营养及临床应用....................................................................... 17感染性休克............................................................................................. 22急性呼吸系统感染抗生素合理使用.............................................................. 25小儿心力衰竭诊断与治疗 (33) 新生儿呼吸窘迫综合征的表面活性物质替代指南 (38) 新生儿持续肺动脉高压诊疗常规 (42) 新生儿肺出血诊断与治疗方案………………………………………………………….. 44新生儿常频机械通气常规………………………………………………………………… 45新生儿HIE诊断标准…………………………………………………………………….. 47新生儿危重病例评分………………………………………………………………………48新生儿窒息复苏指南……………………………………………………………………… . 50新生儿心电图……………………………………………………………………………… 54新生儿败血症诊疗方案…………………………………………………………………… .61

儿科指南目录(中文)

1.儿童支气管哮喘诊断与防治指南（2016年版） 2.小儿神经源性膀胱诊断和治疗指南2015 3.儿童骨髓增生异常综合征诊断与治疗中国专家共识（2015年版） 4.儿童流感诊断与治疗专家共识（2015年版） 5.中国儿科超说明书用药专家共识（2016年） 6.新生儿窒息诊断的专家共识 7.儿童过敏性紫癜循证诊治建议 8.儿童肺炎支原体肺炎诊治专家共识（2015年版） 9.2015国际小儿急性呼吸窘迫综合征专家共识解读 10.儿童急性中耳炎诊疗——临床实践指南（2015年制定） 11.流行性感冒抗病毒药物治疗与预防应用中国专家共识 12.手足口病诊疗指南(2013年版) 13.性早熟诊疗指南(试行) 14.儿童高铅血症和铅中毒预防指南 15.儿童高铅血症和铅中毒分级和处理原则 16.中国儿童普通感冒规范诊治专家共识（2013年） 17.中国０至５岁儿童病因不明急性发热诊断和处理若干问题循证指南（标准版）2016年 18.中国０至５岁儿童病因不明急性发热诊断和处理若干问题循证指南（简化版）2016年 19.新诊断儿童癫痫的初始单药治疗专家共识（2015年）

20.免疫异常儿童疫苗接种(上海)专家共识 21.新生儿高胆红素血症诊断和治疗专家共识（2014年） 22.中国新生儿复苏指南（2016年北京修订） 23.足月儿缺氧缺血性脑病循证治疗指南（2011-标准版） 24.儿童急性淋巴细胞白血病诊疗建议（第三次修订草案） 25.儿童急性淋巴细胞白血病诊疗建议(第四次修订) 26.儿童缺铁和缺铁性贫血防治建议 27.儿童血友病诊疗建议 28.儿童获得性再生障碍性贫血诊疗建议 29.儿童非霍奇金淋巴瘤诊疗建议 30.尿路感染诊断与治疗中国专家共识（2015版） 31.尿路感染诊断与治疗中国专家共识（2015版）-复杂性尿路感染医脉通LOGO 32.尿路感染诊断与治疗中国专家共识（2015版）-尿路感染抗菌药物选择策略及特殊类型尿路感染的治疗建议 33.儿童夜间遗尿症诊治指南 34.2014年中国儿童单症状性夜遗尿疾病管理专家共识 35.儿童脓毒性休克（感染性休克）诊治专家共识（2015版） 36.免疫功能异常患儿的预防接种专家共识(试行稿)：原发性免疫缺陷病 37.儿童晕厥诊断指南（2016年修订版） 38.儿科支气管镜术指南(2009年版)

新生儿转运工作指南

新生儿转运工作指南新生儿转运(nｅonatal transport,NT）就是危重新生儿救治中心(newborn ｃare ceｎｔｅr,NCＣ)得重要工作内容之一，目得就是安全地将高危新生儿转运到ＮCC得新生儿重症监护病房（ｎeonataｌ inｔeｎsi ｖｅ cａre unit,NIＣU)进行救治，充分发挥优质卫生资源得作用。然而,转运过程中可能存在患儿病情变化与死亡得风险，要实现安全、快速地转运，必须规范与优化NT工作,以达到降低新生儿病死率得目得。因此,结合近几年转运工作得新进展新经验,本指南对２013年版《中国新生儿转运指南》进行更新与完善，以供新生儿医师参考。 1 建立区域性新生儿转运网络(rｅｇｉonａl neonatal transｐort nｅtwoｒk,RNTN） RＮTＮ就是由区域内不同等级得NＣC与相关医疗保健机构组成，以ＮCC为中心，集转运、救治、研究与培训为一体得特殊医疗服务系统.网络关系见图。

（1）较高等级得RNTN可包含较其低等级得RNＴN。后者可依次作为前者得分系统或子系统，既参与整个系统得运作，又组织各自局部系统得运作。NCC应遵照其层级所定义得医护服务条件与能力接收新生儿,一般病情患儿提倡按NＣＣ等级逐级实施转运,特殊病情患儿可根据需要越级实施转运. (2）确定RＮＴN得范围应以"适宜、就近"为原则,在行政区划得基础上兼顾地方就医习惯与地理距离。有条件得情况下,同一区域可同时有多个RＮＴN提供服务;不要求RNＴN中NCＣ与转出医疗机构之间就是专属关系，可允许与其她RNTN之间有交互联系。 (３)RNTN所服务区域得大小受其层级限制，结合地理形态、人口密度、气候条件、区域经济、医保支付与可提供适当服务得NCC数量等综合考虑。采用救护车转运，RNTN服务半径一般以20０~４0０ km为宜，除确认患儿病情许可且必须转运外，超出此范围应选用其她更高速得交通工具。（4)RNTN采用＂综合、主动、全程、立体型”技术服务模式为宜.业务内容应为涵盖高危儿转运救治、人员培训与科学研究得全方位服务,转运形式以ＮCC接回患儿得主动转运为主,转运得服务范围应包括产房待产、新生儿转运与宫内转运,转运途径应逐步拓展为陆路、航空与水路结合得立体型交通网. ２NT得队伍建设２、1 NＴ机构 NＣC设转运服务台,有条件得应设立转运服务处。其职能主要就是转运组织管理与质量控制. (1)预备管理：转运车辆、设备与药品等由转运处统一管理,应每天检查物品完备完好情况。车辆设备应做好定期保养,发现故障隐患应及时维修,使其时刻处于良好备用状态. (2)过程管理:实行24 h值班制,及时合理调度车辆与人员。实行转运人员亲笔签到制度，以督导及时出发。与转运任务中相关人员保持随时联系以准确掌握动态.

市儿童医院新生儿转运制度及实施细则附流程图

新生儿转运制度及实施细则附流程图一、为适应新形式下对危重新生儿转运要求，提高危重新生儿转运安全性及抢救成功率，提高我院新生儿专业辐射力及影响力，参考徐州儿童医院120急救转运管理制度，结合新生儿转运特点，制定新生儿内科/NICU 新生儿转运制度。二、成立新生儿病区“新生儿转运”管理小组组长：李振光主任副组长：吴宏伟副主任、郝祥梅护士长成员：医疗组：王伟、高继生、刘金凤、杨夏、尚培薇护理组：王妍妍、苗晓、舒长华、叶娅、宋培培三、出诊医生接到转运电话后，详细询问患儿一般情况（姓名、性别、日龄、孕周）、转诊原因及目前患儿病情情况，并评估、解释、记录，告知对方转运风险及相关费用。四、通知护士、司机，启动转运程序，药、物、设备检查齐全；根据病情确定出诊时应配备的特殊抢救器械及药物，3分钟内出发。120转运电话要求保持24小时畅通，保障与对方电话联系；五、到达目的医院首先听取当地医生病情介绍；检查患儿情况，再次评估患儿病情，是否适合转运；将患儿病情及评估结果告知家长，说明风险，签订转运同意书，1-2名家长随车。六、不适合转运的患儿向家人仔细解释，家人理解后签署拒绝转运；特殊病人，如转运风险较大，或与当地医院有潜在医疗纠纷者，应及时上报李振光科主任或院总值班。

·标准·方案·指引·新生儿转运工作指引2017版

· 标准·方案·指南· 新生儿转运工作指南（2017版）中国医师协会新生儿科医师分会　孔祥永　封志纯　李秋平　常立文　陈超　陈倩程秀永　丁国芳　冯琪　付雪梅　高喜容　何少茹　何振娟　李莉　李杨方　李占魁林新祝　林振浪　刘翠青　刘俐　刘玲　卢宪梅　毛健　母得志　史源　孙建华童笑梅　王斌　伍佰祥　夏世文　严超英　杨传忠　杨杰　姚建宏　俞惠民岳少杰　张雪峰　郑军　周伟　周晓玉新生儿转运（neonatal transport ，NT ）是危重新生儿救治中心（newborn care center ，NCC ）的重要工作内容之一，目的是安全地将高危新生儿转运到NCC 的新生儿重症监护病房（neonatal intensive care unit, NICU ）进行救治，充分发挥优质卫生资源的作用。然而，转运过程中可能存在患儿病情变化和死亡的风险，要实现安全、快速地转运，必须规范和优化NT 工作，以达到降低新生儿死亡率的目的［1-5］。因此，结合近几年转运工作的新进展新经验，本指南对2013年版《中国新生儿转运指南》进行更新和完善，以供新生儿医师参考［6］。 1　建立区域性新生儿转运网络(regional neonatal transport network，RNTN) RNTN 是由区域内不同等级的NCC 和相关医疗保健机构组成，以NCC 为中心，集转运、救治、研究和培训为一体的特殊医疗服务系统［1-4］。网络关系见图1。 1.1　较高等级的RNTN 可包含较其低等级的RNTN 。后者可依次作为前者的分系统或子系统，既参与整个系统的运作，又组织各自局部系统的运作。NCC 应遵照其层级所定义的医护服务条件和能力接收新生儿，一般病情患儿提倡按NCC 等级逐级实施转运，特殊病情患儿可以根据需要越级实施转运［6-7］。 1.2　确定RNTN 的范围应以“适宜、就近”为原则，在行政区划的基础上兼顾地方就医习惯和地理距离。有条件情况下，同一区域可同时有多个RNTN 提供服务；不要求RNTN 中NCC 与转出医疗机构之间是专属关系，可允许与其他RNTN 之间有交互联系［1］。 1.3　RNTN 所服务区域的大小受其层级限制，结合地理形态、人口密度、气候条件、区域经济、医保支付和可提供适当服务的NCC 数量等综合考虑。采用救护车转运，RNTN 服务半径一般以200～400 km 为宜，除确认患儿病情许可且必须转运外，超出此范围应选用其他更高速的交通工具。 1.4　用RNTN 采用“综合、主动、全程、立体型”技术服务模式为宜［3-8］。业务内容应为涵盖高危儿转运救治、人员培训和科学研究的全方位服务，转运形式以NCC 接回患儿的主动转运为主，转运的服务范围应包括产房待产、新生儿转运和宫内转运，转运途径应逐步拓展为陆路、航空和水路结合的立体型交通网。2　NT 的队伍建设 2.1　NT 机构　NCC 设转运服务台，有条件的应设立基金项目：国家卫生和计划生育委员会妇幼司，联合国儿童基金会（CHINA-UNICEF501MCH ）通讯作者：封志纯（Email ：zhjfengzc@https://www.doczj.com/doc/f912271164.html, ）图1 区域性新生儿转运网络示意图注：NCC ：新生儿救治中心（newborn care center ）

新生儿工作流程

权责单位作业流程简要说明表单文件

产科医生产科医生新生儿医生新生儿医生产科医生新生儿医生助产士新生儿医生新生儿医生新生儿医生护士新生儿医生护士新生儿医生新生儿医生护士新生儿医生护士新生儿医生护士新生儿医生护理部收银部指妊娠满28周以上（或胎儿体重≥1000克以上）母亲进入临产状态的胎儿。孕次产次、孕周、是否多胎、胎儿预估体重、羊水情况、母亲情况、胎监情况、是否麻醉、其他可能影响胎儿的情况高危儿：早产、多胎、低体重、宫内窘迫、产前子痫、糖尿病、先天畸形接生程序：做好接产前的准备工作，开启远红外保暖床，检查、连接各类必须物品（氧气、吸引器、抢救箱、血型检验管等等），并让这些物品处于备用状态。婴儿娩出后先清吸婴儿口鼻液体，建立呼吸，同时评价婴儿情况。如果评价婴儿情况良好由护士断脐，然后称重、包裹并将婴儿抱给陪伴家属。评价呼吸、心率和肤色判断是否需要转上一级医院进一步检查治疗需要心电监护和氧饱和度监护的留置婴儿室观察包括置暖箱，吸氧、输液、洗胃、鼻饲、兰光光疗等新生儿医生反复评判治疗效果转院由新生儿医生决定、联系，由接收医院专车转运。可在婴儿沐浴时查体、经皮测胆红素测定，护士按医嘱进行血糖监测，预防接种等由新生儿医生和护士分别交待宝宝出院后护理要点，完成听力筛查和代谢病筛查，需要返回复诊的预约时间，打印出院小结和填写宝宝手册。新生儿窒息抢救规范新生儿处理规范危重新生儿转运规范新生儿免疫接种规范新生儿光疗规范新生儿科查房规范新生儿听力测试流程规范新生儿先天性疾病筛选流程规范围产儿死亡评审制度围产儿死亡报告制度围产儿抢救程序接生程序高危儿产前评估转院？沐浴、体检、疫苗接种、治疗、记录普通儿转院出院评价疗效婴儿室留观治疗母婴同室新生儿筛查出院宣教、出院小结、预约返回死亡评价 Y Y N N 筛查否？ N Y N

3.《危重新生儿救治中心建设与管理指南》

《危重新生儿救治中心建设与管理指南》（国家卫生计生委办公厅2017年12月8日) 第一章总则第一条为指导和加强危重新生儿救治中心建设与管理，构建区域性危重新生儿救治体系，提高新生儿疾病救治能力和水平，保证医疗质量和安全，根据《中华人民共和国母婴保健法》、《中国儿童发展纲要（2011-2020年）》、《中华人民共和国执业医师法》、《医疗机构管理条例》和《护士条例》等有关法律、法规，制定本指南。第二条危重新生儿救治中心是指医疗机构内独立设置的，以新生儿病房和新生儿重症监护病房为依托实体，具有危重新生儿监护诊疗能力，承担区域内危重新生儿救治、转运、会诊和新生儿专科技术培训、指导任务的临床单位。第三条各级卫生计生行政部门应当加强对医疗机构危重新生儿救治中心建设、管理的指导和检查，促进危重新生儿救治中心工作标准化、规范化和科学化。第二章区域组织管理第四条危重新生儿救治中心按照服务能力基本要求（附件1）分为省（区、市）、市（地、州）、县（市、区）三级。各级危重新生儿救治中心的认定由本级卫生计生行政部门组织，建立由上级专家参加的评审委员会，采用材料审核和现场评估的方式确认。第五条危重新生儿救治中心的设置应当符合区域医疗卫生服务体系规划，遵循择优确定、科学布局、分级诊疗的原则。（一）地方各级卫生计生行政部门应当根据医疗机构设置规划和新生儿诊疗需求，对区域内危重新生儿救治中心的数量和布局进行统筹规划。（二）医疗机构可以根据区域医疗服务需求、区域卫生规划和医疗机构设置规划，结合自身功能定位确定危重新生儿救治中心服务能力的层级目标。（三）原则上所有的省（区、市）、市（地、州）、县（市、区）行政区域应当至少设立1个服务能力不低于相应层级的危重新生儿救治中心。第六条各级行政区域应依托危重新生儿救治中心建立健全危重新生儿救治协作网，参照新生儿转运工作指南开展转运工作。所有开展危重新生儿医疗服务的机构，超出技术能力范围或床位满员时，应当及时将患儿转运至适宜的危重新生儿救治中心，以保证区域内每个新生儿均能及时获得适当的医疗与护理服务。

危重新生儿转运与护理

危重新生儿转运与护理发表时间：2017-08-23T13:47:26.803Z 来源：《心理医生》2017年19期作者：罗玲苏昕黄磊（通讯作者）[导读] 成功的转运不仅能降低新生儿的死亡率，而且可以为新生儿接受进一步的治疗奠定基础，从而减少新生儿的不良结局，改善其预后。（四川大学华西第二医院新生儿科出生缺陷与相关妇儿疾病教育部重点实验室四川成都 610041）【摘要】国外20世纪70年代已经开始危重新生儿的转运工作，我国新生儿转运起步较晚。本文综述了危重新生儿转运的指征、转运前的处理、转运过程中的护理要点。【关键词】危重新生儿；转运；护理【中图分类号】R473.72 【文献标识码】B 【文章编号】1007-8231（2017）19-0210-02新生儿转运是接收单位主动“把流动的新生儿重症监护病房（NICU）送到危重患儿身边”的双程转运系统[1-2]，目的是安全地将高危新生儿转运到NICU进行救治，充分发挥优质卫生资源的作用。成功的转运不仅能降低新生儿的死亡率，而且可以为新生儿接受进一步的治疗奠定基础，从而减少新生儿的不良结局，改善其预后[3]。 1.转运人员组成应设立专门的新生儿转运队伍，由新生儿科医师、新生儿科护士和司机至少各一名组成转运小组，可加入呼吸治疗师等成员。根据区域内转运工作量的大小，有时需设立多个转运小组以保证转运工作的及时和顺利完成。所有人员均经过新生儿转运的专业培训，并具备良好的组织沟通协调能力。 2.转运对象出生体质量<1500克或孕周<32周；严重的出生窒息，复苏后仍处于危重状况；需要机械辅助通气；先天畸形需要立刻外科手术治疗；严重感染、黄疸需要换血等[4]。 3.转运前准备通知司机准备新生儿转运车。车内配备新生儿转运暖箱、转运呼吸机、T组合复苏器、心电监护、血糖仪、输液泵、氧气、负压吸引装置、转运急救箱。转运急救箱内准备有留置针、注射器、葡萄糖水、生理盐水、吸痰管、胃管、喉镜、气管导管、复苏囊、常用急救药品等。转运结束时应将使用过的抢救物资及时补充以备用。转运队伍到达后医生为患儿查体，并告知家属目前病情、转运风险并签知情同意书。护士将患儿抱入已预热的转运暖箱里，连接心电监护及各管道，并保持通畅。若有动静脉置管应认真填写交接单。采用STABLE（sugar，temperature，assisted breathing，blood pressure，labworks，emotional support)技术进行转运前处理[5]，使患儿生命体征处于最佳平稳状态。据报道，在危重新生儿转运护理中运用“STABLE”技术可增加转运成功率，降低转运途中新生儿死亡的风险[6]。 4.转运中护理4.1 保暖新生儿由于体表面积相对较大，皮肤薄，血管较多，易于散热，同时体温调节中枢发育不完善，容易发生低体温。低体温可以导致新生儿寒冷损伤，引起新生儿硬肿症以及心、脑、肝、肾和肺等重要脏器损伤，甚至死亡。据报道44%-56.1%的极低出生体重儿会在转运途中出现低体温[7]。患儿应放入预热好的暖箱，并根据患儿日胎龄、日龄，体质量调节箱温。 4.2 保持呼吸道通畅颈部可垫一软枕，头偏一侧防止呕吐误吸，有分泌物应先吸痰。必要时采用T组合复苏器或呼吸机辅助通气，自动充气式复苏囊因操作者经验不同，人工通气时输出的吸气峰压存在很大差异，每次输出的压力也不同[8]，且加压过程中容易导致气管插管脱出[9]，T组合复苏器能够根据需要精确地调节，保持恒定一致的吸气峰压并能提供精确而恒定的呼吸末压[10]。妥善固定气管导管，保证呼吸机管道无打折，观察患儿胸廓起伏是否一致。 4.3 保持静脉通道通畅根据病情需要可建立静脉双通道便于抢救，妥善固定，随时观察输液部位情况。 4.4 维持血糖正常有研究表明转运中血糖异常发生率很高，监测和处理有助于降低新生儿血糖异常的发生率，及早维持患儿血糖在正常范围内[11]。低血糖可使脑细胞失去基本能量来源，导致脑代谢和生理活动无法进行，如不及时纠正会造成永久性脑损伤[12]，高血糖严重者致颅内出血和脑室周围白质软化。 4.5 严密观察患儿生命体征注意监测心率、呼吸、血压、血氧饱和度，如有病情变化及时处理。转运即将到达时转运小组电话通知本单位NICU医护人员，介绍患儿病情，以便为患者提供连续的抢救治疗做好充足准备。 4.6 心理护理安抚患儿家属的焦虑情绪，保证护理措施的顺利实施[13]。 5.转运后管理患儿到达后，应由绿色通道直接送入NICU，NICU值班人员先妥善安置患儿，稳定患儿病情，进行必要的处置，同时，转院人员需与NICU值班人员进行交接，将当地医院的所有资料交给NICU值班人员，详细介绍患儿转运全过程的情况。待患儿病情基本稳定后，协助交代家长办理入院手续，并完成进一步详细询问病史，完成各种知情同意书的告知并签字。转运人员完善转运记录单，详细检查已使用过的转运设备，清点药品、物品，补充氧气及其他耗材，做好消毒处理，以备下一次使用。转运系统的主要功能是妥善地将高危新生儿转运到适宜的NICU进行救治，转运人员应该有过硬的操作技术，良好的应变能力，高度的责任心。有效的院前护理抢救是危重新生儿转运成功的关键[14]。成功的转运不仅能降低新生儿的死亡率，而且可以为新生儿接受进一步的治疗奠定基础，从而减少新生儿的不良结局，改善其预后。【参考文献】

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