December 2010, 17(Suppl. 2): 79–83
https://www.doczj.com/doc/9f8231047.html,/science/journal/10058885 https://www.doczj.com/doc/9f8231047.html,
The Journal of China Universities of Posts and Telecommunications
A self-adjustment QoS architecture for wireless sensor networks
XIE Dong-liang ( ), WANG Feng-hua
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
Abstract
An architecture featured in quality of service (QoS) online self-adjusted measurement and control for wireless sensor networks (WSN) is proposed in this paper. Unlike traditional end to end (E2E) QoS definition, many new characteristics are presented in WSN, especially data-centric and application driven. Based on exploration of WSN QoS definition and typical traffic model, we design a dynamic QoS guarantees platform, which achieves online protocol self-adjustment to get optimization performance. The architecture is verified by a practical system designed for environment monitoring.
Keywords WSN, QoS, Architecture
1 Introduction QoS is an important issue for WSN. But inherent complexity and the applications diversity of WSN make QoS cannot be defined as the traditional End to End internet, in which QoS parameters adhere to time delay, jitter, packet loss rate, throughput, fairness, et al. So the new QoS guarantee architecture needs to be explored to adapt to the features of WSN.
To realize this vision, D Chen and M Younis [1–2] review the techniques for QoS support in general wireless networks, analyze new QoS requirements of a wide variety of applications classified by data delivery models in WSN, and propose some non-end-to-end QoS parameters. But they didn't notify the nature factor which influence the performance, and also not give the clear QoS definition for these applications. At the same time, many simulation platform for WSN are developed, including J-Sim (formerly known as JavaSim) jointly developed by Ohio state university and the university of Illinois, EWSNSim from Twente university in Holland, Mannasim from UFMG university in Brazil, WSNsim of Zhejiang university and Tossim from Crossbow in USA. From above, Tossim and EWSNSim are for especial WSN system. They all achieve modeling and simulation for certain
Received date: 1-12-2010
Corresponding author: XIE Dong-liang, E-mail: xiedl@https://www.doczj.com/doc/9f8231047.html, DOI: 10.1016/S1005-8885(09)60578-1
protocols of WSN. But none of them have noticed the related features according to the peculiar application in WSN. The main purpose of simulation is still concerned on end-to-end
transmission delay, bandwidth, et al, but not to give the essential description for QoS parameters.
In this paper, we propose a new QoS guarantee architecture, shown in Fig.1. Based on WSN QoS definitions and formalism description, we put forward mapping relationship between QoS parameters of WSN and network parameters. Then, we designed a QoS guarantee architecture featured by the dynamic QoS evaluation subsystem which not only collect the actual network performance by measurement, but also achieve the parameters by simulation online for better performance.
80 The Journal of China Universities of Posts and Telecommunications 2010
2 QoS model in WSN
2.1QoS definitions in WSN
The main application of WSN is to transport date collected from deployed nodes to user for the external events judgment. Then unique characteristics of WSN, such as extremely resource-constrained sensors, large-scale random deployment, and novel data-centric communication protocols, lead to unprecedented challenges in the area of QoS support in WSN [3]. The traditional QoS parameters, such as time delay, bandwidth, congestion, packet loss rate, cannot fully reflect the performance, so we focused on the new QoS requirement. Based on [1–2], five QoS definitions are listed as follow:
1)Ability to provide valid data. It is influenced by topology, connectivity, coverage and traffic capacity, energy consumption and so on.
2)Handling delay: the speed to detect and report event. The reaction time is affected by accuracy of node detection, transmission delay, and decision algorithm.
3)Lifetime: the period of persistent service. It is affected by topology, connectivity, energy consumption and so on.
4)Network survivability: ability of automatic restoration. It depends on deploying density of nodes and routing protocol.
5)Decision accuracy: Decision made by users depends on the quantity of data arrived, transmission delay, decision algorithm and so on.
2.2 Traffic types
Requirements are different for multi-application and diverse protocol. Here we abstract WSN on the base of [2].Three types of data traffic model are concluded as follows.
1)Discrete-burst traffic: The characteristics are burst transmission by certain nodes, such as pre-alarming of event-driven.
2)Discrete-continuous traffic: Data transmission to sink is at a low frequency. It generally refers to environmental monitoring.
3)Continuous traffic: During this period, data transmission is of a fixed frequency.
2.3 Mapping of QoS parameters and network parameters
QoS parameters show how the end-users feel about the network service, but it finally turn to network parameters. On handling QoS traffic in WSN, the mapping relationships between QoS parameters and network resources should be analyzed firstly, and corresponding adjustment will be configured to the actual network to guarantee the WSN QoS. Network parameters of WSN could be measured actively and or passively, such as topology, link delay, packet loss rate, residual energy of node, buffer size limitation, congestion and so on. QoS parameters of WSN are application specific, which reflect the tussle interactivities of many different network resources, such as bandwidth, delay, and energy consumption rate and so on. For example, in event-driven situation, the response time contains time from the beginning of event to the correct judgment made on the basis of collected data. The contributors contain not only time delay of packet from node to user, but also quantity of data as judgment basis, decision accuracy, nodes with source data, transmission delay and so on. The relationship among the above elements should be considered. In the practical applications, the decision accuracy will be defined in advance. Then, in order to make alarm in time, the parameter of delay will be the main contributors to the QoS guarantee. That will be adjusted to improve network performance. Moreover, when the main function of WSN shifted to the ordinary environment continuous monitoring, the main QoS contributors need to be varied accordingly.
3 WSN QoS guarantees platform
The WSN QoS platform supporting multi-application is a mixed system with evaluation, control and management. It is able to maintain their operation automatically. There are three subsystems: evaluation subsystem, control subsystem and management subsystem. Evaluation subsystem makes a decision about whether the current performance is accord with the requirement on the basis of collected data. If not, main contributors of QoS will be selected. Evaluation subsystem will operate a QoS adjustment strategy to control subsystem, which deploys the new QoS parameters to practical WSN nodes. To guarantee the performance, the control subsystem relied on the active and passive measurement module. Two interfaces are included: one is the interface between sink and network by which network resources are controlled; the other one is the interface for user by which end-user could manage QoS parameters. The structure of the QoS guarantee platform is showed as Fig. 2. A detailed description of each subsystem will be present as following.
Supplement 2 XIE Dong-liang, et al. / A self-adjustment QoS architecture for wireless sensor networks 81
Fig. 2Structure of QoS guarantee platform for WSN
3.1 Evaluation subsystem
As the core of QoS guarantee platform, evaluation
subsystem makes the decision that whether QoS requirements
are satisfied. If not, QoS adjustment strategy will be operated.
The functional structure of evaluation subsystem is showed
in Fig. 3. Application module (AM), network simulation
module (NSM) and mapping module (MM) of QoS
parameters and network resources are contained. There are
three interfaces including interface to management subsystem,
interface to control subsystem and interface to user.
82 The Journal of China Universities of Posts and Telecommunications 2010
visualization interfaces, shown as Fig. 4.
Fig. 5 Emergency environmental monitoring based on WSN
Fig. 6 Snapshot of QoS guarantees
5 Conclusions
The paper presents a QoS architecture for WSN which
achieves online programming and self-adjustment. WSN are
highly application oriented. While the solution or protocol
achieves a good performance on the scenario, it may be
poorly suited to other configurations. Therefore, it is hardly to
draw the general solution for WSN QoS mechanisms. How to
map the QoS parameters with network resources is the basic
problem in WSN QoS research field. Maybe the middleware
mechanism will be a particle solution.
Acknowledgements
This work was supported by the China major projects of the
wireless mobile communications network (2010ZX03006-002-03,
2009ZX03006-006).
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