Mobile Agent Interoperability Revisited
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移动代理Mobile Agent在智能网络管理系统中的作用作者:颜吉军来源:《智富时代》2017年第08期【摘要】随着科学技术的进步,我国网络运用的规模也呈现出不断扩大的趋势,这就对我们的网络管理提出了一种新的要求,然而传统的集中式的网络管理模式已经不能够满足当前我国网络管理的需要,而一种新的网络管理模式为我国日益扩大的网络需求带来了新的管理思路,这就是分布式网络管理技术。
【关键词】网络管理;智能化;移动代理一、网络管理概述网络管理的根本目标就是能够满足用户对网络的具体需要,这就包括有效性、安全性、综合性等各方面的具体要求。
当前网络管理系统主要有集成化管理、智能化管理和分布化管理三种方式。
目前的网络管理系统都是基于SNMP协议,管理模式单一,随着网络管理越来越复杂,其局限性日益明显地攀露出来:(一)集中式管理。
集中式管理虽然也能够达到一定的网络管理的需求,但是集中式管理存在着管理可靠性差的问题,只要我们的管理者出现了故障,将会极大的影响我们的网络管理系统,从而使网络处于没有管理的状态。
(二)智能化管理。
智能化管理也是网络管理系统的一个方式。
但是智能化管理是通过不间断的轮询来获取当前网络元素的状态,如果网络访问所产生的信息流量变大将会使网络的速度下降,影响用户的上网质量。
同时,由于网络速度的降低将会影响网络管理的时效,造成延时。
(三)分布式管理。
分布式管理是通过不同的网络设备开发商和不同的网络管理系统所形成的一个组合,各个系统和各个网络设备开发商之间很难得形成一个具体的组合来进行统一的管理,因此灵活性较差。
二、基于移动代理的智能网络管理(一)移动代理技术简介移动代理(Mobile Agent)是指一段动态分发到远端主机并在远端主机上执行的程序。
它由移动代理的管理者发布到网络中任何一台具有移动代理运行环境的主机中执行,并返回执行的结果或是相应的信息。
IBM,SUN等公司都制定了相应的策略并推出了产品。
移动办公是提高工作效率的有效途径引言在日益严峻的商业竞争和更加难以预测的市场面前,企业如何才能尽可能地提高并保持其创造力和竞争力呢?这个问题一直困扰着许多的IT企业地管理者。
过去几年IT产业的沉浮兴衰与风云变换使得情况变得越来越复杂。
这就使得IT产业的经营者们不得不在其计算机、应用程序甚至网络构架中采取“额外”的措施来最大限度地提高其自身的工作效率,以期能取得较好的业绩与效益。
许多企业的管理者发现,除了建立映射数据中心和网络备份系统外,“移动办公”也已成为一条提高企业工作效率、促进业务反弹的有效途径。
目前,在商业过程当中,花费在办公室之外的时间越来越多,并且有的业务要分散执行,而公司职员们也分散在总部、分部和甚至是家庭之中。
所以要确保整个企业始终能保持创旺盛的"生产"能力,就应该使企业的每个成员无论身处何处都能够与企业保持联络并能进行有效的工作。
思科公司技术开发部的高级副主管Charlie Giancarlo说:“当用户离开办公桌而处于"移动"过程中的时候,如果他不能够访问其公司的网络资源并能在"移动"中继续办公的话,他就可能丧失某些商业机会。
”为此,思科公司提出了“思科移动办公室”来应对这一挑战,这是一系列技术解决方案,能使IT公司为其职员提供安全、高速的移动连接。
那么“移动办公”的效益何在呢?让我们举一个例子来说明。
航空工业部门对公众旅行制定了越来越来严格的安全规范,以至于许多商业旅行者发现他们在机场的逗留时间越来越长。
如果机场部署了无线局域网,他们就可以通过便携式电脑中的无线局域网适配器和有安全保证的虚拟个人网络客户机软件,安全有效地接入机场的无线局域网,并进而与其公司的网络连接,从而保持了持续办公的能力。
此外,宾馆、会堂也应该为处在移动中的商业人士提供无线或有线以太网连接服务,这样就可保证他们通过因特网访问其公司内部的信息资源。
llm agent提示词规则全文共四篇示例,供读者参考第一篇示例:LLM Agent提示词规则是指在对话系统中,为了提高用户体验和对话效果,制定的一系列提示词的规则。
这些提示词规则是为了引导用户在与对话系统进行交流时能够更加顺利地进行对话,并且提供更加准确的信息。
LLM Agent提示词规则包含了对于一些关键词的设定。
这些关键词通常是用户可能用到的常见词汇,包括询问某个商品的价格、库存情况、配送方式等。
为了提高对话系统的效率,LLM Agent会根据这些关键词的出现频率和重要性来设定相应的提示词规则,从而确保用户可以快速找到需要的信息。
LLM Agent提示词规则还包含了对于用户输入的语义分析。
通过对用户输入的内容进行语义分析,LLM Agent可以更好地理解用户的意图,并给出相应的回答。
当用户询问“有没有折扣优惠”,LLM Agent可以根据这个问题判断用户想了解某个商品是否有优惠,并回答相应的信息。
这种语义分析可以让对话系统更加智能化,提高用户体验。
LLM Agent提示词规则还包括了对于对话流程的控制。
通过设定一定的提示词规则,LLM Agent可以引导用户进行有序的对话,避免出现混乱或冗余的问答。
当用户询问某个商品的价格后,LLM Agent会根据用户的反馈进一步询问用户是否需要购买,从而引导用户完成购买流程。
这种对话流程的控制可以帮助用户更快地找到需要的信息,并提高购买转化率。
第二篇示例:LLM代理提示词规则指的是在进行垃圾邮件过滤和内容识别时,使用一定的关键词或短语来触发过滤规则,从而帮助用户检测或过滤特定类型的邮件。
在进行邮件过滤时,LLM代理提示词规则是一个非常有效的工具,可以极大地提高过滤的准确性和效率。
LLM代理提示词规则的制定需要根据具体的邮件内容和用户需求来进行设计。
一般来说,可以考虑以下几个方面来设置提示词规则:1. 邮件主题关键词:邮件主题通常是用户打开邮件时的第一个信息点,因此在设置提示词规则时,可以考虑邮件主题中包含的关键词来进行过滤。
This work has been fully supported by Vodafone I.T., Research & Development Department, TURKEY.Secure User-Plane Location (SUPL) ArchitectureFor Assisted GPS (A-GPS)Tolga Göze 1, Özgün Bayrak 1, Metin Barut 1, M. O ğuz Sunay 2,1Vodafone IT. Research & Development Department, Istanbul, TURKEY{tolga.goze, ozgun.bayrak, metin.barut}@2Dept. of Electrical & Computer Eng., Koç University, Istanbul, TURKEYosunay@.trAbstract—The aim of this paper is to analysis the new as-sisted GPS (A-GPS) architecture based on SUPL (Secure User Plane Location). This architecture improves perform-ance of A-GPS based location estimation approaches. We provide comparative field test results of the developed sys-tem with the conventional GPS in terms of both the positionaccuracy and the TTFF (time to first fix) delay times. We have also examined the effectiveness of initial position esti-mation on the TTFF and the accuracy of calculated position.Field tests are conducted on a real GSM network in urbanareas and indoor environments. Executed analysis has pro-vided that the developed SUPL based A-GPS system achieves high-performance on estimation accuracy and fast-er TTFF.Key words: SUPL, AGPS, mobile positioningI. I NTRODUCTIONGPS is a satellite-based radio-positioning system that provides navigation and timing information to militaryand civilian users [1]. The GPS satellites continually broadcast almanac and ephemeris data to aid users esti-mate their position, velocity and time. The almanac is the orbital parameters for all the GPS satellites while theephemeris is the precise time and orbital data for the in-dividual GPS satellites. While the almanac data can bevalid for months, the ephemeris is valid for a few hours.Upon receiving the broadcast signals from at least 4 sa-tellites, a GPS receiver can predict its location with highaccuracy. GPS receivers work best in open areas that of-fer an unobstructed line of sight to the GPS satellites. In places where GPS signals are weak, obstructed, or scat-tered, as is the case inside an office building or in an ur-ban canyon, traditional GPS receivers compute positionsintermittently at best and usually not at all.In GPS receivers, the time required to first calculatethe position (time to first fix - TTFF) depends on theavailability of current information at the receiver fromprevious fixes as well as the strength of the available GPSsignals at the location of interest. Thus, TTTF varies sig-nificantly; in hot start, it takes merely seconds but in cold start, depending on the availability and quality of satellite signals, it can sometimes take several minutes. A long TTFF is unacceptable for location-based services or emergency calls.Assisted GPS (A-GPS) techniques have been devel-oped to improve the sensitivity of the GPS reception and reduce TTFF [2-7]. The main idea behind A-GPS is toprovide assistance data to the GPS receiver through a wireless network. With this data, mobile devicesequipped with A-GPS can compute positions more quickly and in much more difficult environments. There are three basic types of data that the assistance servermay provide to the GPS receiver: precise GPS satellite orbit and clock information; initial position and time es-timate; and for A-GPS-only receivers, satellite selection, range, and range-rate information. The location estimatemay also be computed at the assistance server using the feedback data received from the A-GPS receiver. In thiscase, the GPS receiver is left with the sole job of collect-ing range measurements. Depending on where the loca-tion estimation calculations are conducted, A-GPS meth-ods are classified as either mobile-based or network-based.The communication exchange between the mobile device and the A-GPS server may be conducted in one oftwo ways: 1. Control-plane A-GPS: Here, the assistance messagesare sent using explicit, pre-defined cellular network (GSM/WCDMA) signaling structures. The initial A-GPS systems all used the control-plane for the transmission of assistance data. However, as the number of A-GPS capable users increase in the cellular system, there is significant potential of the control-plane A-GPS exhausing the system capacity. 2. User-plane A-GPS: Here, the assistance messages are sent using an IP data connection and thus use a GPRS/EDGE/HSPA connection without requiring any wireless standard specific messaging. The user-plane A-GPS has recently been proposed as an alternative to the control-plane A-GPS to avoid system capacity exhaustion due to assistance related signaling. Even though initial work on A-GPS has focused on control-plane solutions and subsequent standards have been written on both sides of the Atlantic (TIA/IS 801-1,3GPP TS 25.331 and 3GPP2 C.S0022-0-1), extensions to these standards have also been made to cover user-plane based A-GPS solutions (3GPP TS 44.031 and IS-801-A).Cellular system agnostic solutions for the user-plane A-GPS approaches have been developed and standardized by the Open Mobile Alliance (OMA) [8-9-11]. It is envisioned that, due to its inherent advantage in cellularcapacity usage, user-plane based A-GPS solutions will dominate the market. However, currently the user-plane solutions in North America are limited by the fact that simultaneous voice and data feature is non-existent in 2G systems there. This paper is concerned with system development and field test performance evaluation of a user-plane A-GPS system that makes use the Secure User-Plane Location (SUPL) Architecture, a recently standardized system by Open Mobile Alliance (OMA) [9-11]. To the authors’ knowledge, this paper is the first of its kind in presenting an actual, deployed user-plane A-GPS system and associated field test results. To this end, we present in this paper the developed SUPL server, and the SUPL MIDlet for the mobile station for the A-GPS operation. We also present extensive field test measurements to asses the system performance of the SUPL based A-GPS system.The remainder of this paper is organized as follows. In Section II we provide a brief overview of the SUPL architecture. In Section III we describe how we have implemented the A-GPS system using SUPL, describe the deployed SUPL server. In Section IV we analize the effect of initial position accuracy. In Section V we present the SUPL MIDlet we have developed to conduct the system operation at the SET, describe the conducted field tests using the developed system and provide performance results. Finally, we draw conclusions in Section VI.II. O VERVIEW OF THE S UPL A RCHITECTURE The SUPL architecture, as described in [9-11], is composed of two basic elements: a SUPL Enabled Terminal (SET) and a SUPL Location Platform (SLP). The SET is a mobile device, such as a phone or a PDA, capable of supporting SUPL transactions. The SLP is a server or a network equipment stack that handles the tasks associated with user authentication, location re-quests, location-based application downloads, charging, and roaming [9]. The SUPL architecture is illustrated inFigure 1.Figure 1. Overall SUPL Enabled A-GPS ArchitectureThe SUPL architecture utilizes existing protocols, IP connections, and data-bearing channels for GPS assis-tance. SUPL supports two protocols, namely, MLP (Mo-bile Location Protocol) and ULP (User Plane Location Protocol). MLP is used in the exchange of location based service data between SLP and a GMLC, or between twoSLPs. ULP, on the other hand, is used in the exchange of location based service data between an SLP and a SET. The SUPL architecture is flexible in terms of the assis-tance data to be exchanged; depending on the capability of the mobile station as well as the specific request from it, the contents of the assistance data may vary [9-10]. III. I MPLEMENTATION OF THE S UPL A RCHITECTURE At Vodafone Turkey, we have developed a mobile lo-cation center solution composed of a Gateway Mobile Location Center (GMLC) and a Serving Mobile Location Center (SMLC). The SUPL Location Platform (SLP) is part of the GMLC in this design and is responsible of handling secure user plane location technologies. It main-ly utilizes user plane data bearers for transferring location information and carrying positioning technology related protocols between a SET (SUPL Enabled Terminal) and the network. It manages the SET initiation, security, posi-tion calculation, assistance data retrieval from Worldwide Reference Network and delivery to SET for user plane location operations.In this design, when the SET initiates a location esti-mation request, the sequences of events that take place are illustrated in Figure 2. A brief summary of each stepof operations is given below.Figure 2. Overview of the SET-Initiated A-GPS process1. The World Wide Reference Network (WWRN) con-tinually tracks the entire global GPS constellation using a number of Hubs at geographically different locations and stores the raw-GPS data. Currently, a number of com-mercial WWRNs are present and our developed SUPL Location Platform (SLP) utilizes one of these existing networks. The developed SLP periodically requests the complete GPS satellite raw-data from the WWRN. In our design, the connection between the WWRN and MLC is established using a VPN or an SSH connection over the public Internet.2. The raw GPS satellite data includes the almanac, ephemeris, reference time, acquisition assistance data, UTC model parameters, real-time integrity and iono-sphere models. The MLC, upon receiving this data, for-mats it into a form as required by the SET and stores it in the SLC cache.3. For the SET initiated scenario, if the SET is not already attached to Packet Data Network services it will attach itself as GPRS, EDGE or others. The SET may reuse the secure IP connection of an already ongoing SUPL session between the SET and the SLP. Thus the SUPL Agent on the SET can start a request for position.4. The SUPL Agent uses the 'Positioning Server Address' provisioned by the Home Network to establish a secure IP connection to the SLP and sends a SUPL START mes-sage to start a positioning session with the SLP. The SUPL START message contains session-id, SET capa-bilities, location identifier (lid) and the optional parame-ter is the desired quality of position (QoP).The SET capabilities include the supported positioning technology (e.g., SET-Assisted A-GPS, SET-Based AGPS, autonomous GPS), preferred method (agpsSETas-sistedPreferred, agpsSETBasedPreferred, noPreference) and associated positioning protocols (e.g., RRLP, RRC, TIA-801). In this implementation SET-Based A-GPS positioning method and RRLP protocol is used. Gsm Cell Information parameter is the location identifier and it contains MCC, MNC, LAC, cell-id and optionally pro-vides NMR and TA information. According to maxLo-cAge parameter in QoP if the last calculated position is up-to-date and reasonably accurate position estimate at the SLP then SLP sends the position to the SET in the SUPL END message.5. The parameter Cell-id which is the parameter of the location identifier is queried from the database in the GMLC side to provide a latitude and longitude as an ini-tial position for the position calculation.6. The SLP sends a SUPL RESPONSE message to the SET, which determines the posmethod consistent with the SUPL START message including posmethod(s) and con-tains a unique compound session-id that is formed from the IP address allocated by the SET and SLP address al-located by the SLP. This compound session-id will be used in all of the remaining messages between the SET and the SLP.7. After receiving the SUPL RESPONSE message, the SET sends a SUPL POS INIT message to the SLP with the mandatory parameters as SET capabilities and loca-tion identifier. Different from the SUPL START mes-sage, it contains the Requested Assistance Data element. The assistance data element optionally provides the pa-rameters almanac, utc model, ionospheric model, dgps corrections, reference location, reference time, acquisi-tion assistance, real-time integrity and navigation model. The SET may provides its position, if this is supported. 8. The SLP sends a SUPL POS message to the SET to start the positioning procedure based on the initial posi-tion which is sent by the GMLC. If the location of cell-id can not found as an initial position in the database then the position is taken from the parameter of the SET. The SUPL POS message contains the PosPayLoad element which is the rrlpPayload as an octet string. RRLP mes-sage contains the Measure Position Request with Assis-tance Data. The performance of the SET depends on the number of satellites included in the assistance data it re-ceives. On the other hand, it is not necessary to send all satellites ephemeris data every time. It causes the slowly location calculation. Thus the initial position is used to select the suitable satellites in view for the SET. Besides the initial position from the SET, cell-id and mobile country codes (MCC, MCC) can be used to select best satellites.Thus the SET calculates the position estimate based on assistance data obtained from the SLP and sends the re-sponse with SUPL POS message. This time rrlpPayload message contains the RRLP Measure Position Response to return the location information [8].9. Once the position calculation is complete the SLP sends the SUPL END message to the SET informing it that no further positioning procedure will be started and that the location session is completed. Both the SET and SLP release all resources related to this session including the secure IP connection [9].IV.I NITIAL P OSITIONThe effect of initial position on AGPS receiver per-formance is investigated in this section. The receiver can use the initial position and uncertainties to determine the satellites in view, reduce its search space and initialize the navigation solution.There are four different approaches to calculation of the SET initial position:1. Getting initial position from the SET:If the last calculated position is up-to-date which is checked with maxLocAge parameter in QoP, then the reference position from the SET as used the initial posi-tion.2. Cell ID + Signal Strength positioning method:In this method, GSM cell information parameter is used. According to our network statistics, the SET is generally close to the BTS, thus an initial position for the SET can be approximated by the BTS location. Statistic results for TA averages shown in Figure 3.Figure 3. Averages of TA Values in Local Network3. Using only Cell ID location:If the NMR information isn’t present in the optional pa-rameter, then the only cell location is used as the initial position.4. Using country code (MCC-MNC) without Cell ID: Finally, if the Cell ID cannot be found in the database, then the country code (MCC-MNC) is used to locate the initial position as the middle point of the country loca-tion.The Cell ID + signal strength positioning method for GSM requires information of the serving sector direction and sectorization scheme of the BS in addition to coordi-nates of the serving Base Station. This method basically estimates the handset's coordinates by combining Cell Identity (CI), Timing Advance (TA, used to estimate the distance between MS and serving BTS), and strongest neighbor cells measurements of the strength of signals received by the Mobile Station (MS). This system deter-mines the mobile phone position based on the intersection of the distance circles. The Cell ID + signal strength posi-tioning method for GSM requires information of the serv-ing sector direction and sectorization scheme of the BS in addition to coordinates of the serving BS. One BTS usu-ally covers a single pointing azimuths 120 degree sector of an area. Usually a tower with 3 BTSs accommodate all 360 degrees around the tower. The TA value is normally between 0 and 63, and changes for each 550m. TA value allows for rough position estimation. Position error can be 550m for TA0, and more than 35km for TA64. Initial position estimates by TA values and TA ranges for sector cell shown in Figure 4.Figure 4. Initial position estimation by TA rangesIn order to investigate the effect of range between user and reference point, distance was set to 0.5 km, 2 km, 5 km, 10 km, 25 km and 35 km, respectively. The average TTFF for each user to reference point distance tested is shown in Figure 5. Obviously, as the user to reference distance increases, the TTFF also increases. Table I shows the accuracy errors. When the user to reference distance increased more than 10 km, a significant in-crease in the TTFF was noticed. Initial position with the accuracy at the level of 500m-2km significantly improves the AGPS TTFF delay and the position estimation accu-racy.Figure 5. The effect of initial position accuracy on the TTFFTABLE IACCURACY ERRORS FOR DIFFERENT REFERENCE POSITIONDISTANCE IN INDOOR AREAS.Mobile Terminal to InitialPosition Distance(km)Accuracy Error (m)0.5 82 105 1215 1425 1735 23V.F IELD T ESTS AND P ERFORMANCE R ESULTSWe have conducted extensive field tests to assess the performance of the developed SUPL A-GPS architecture. The system performance metrics were chosen as TTFF and position accuracy. Data were collected in various geographical areas within Istanbul covering different sce-narios, namely, shopping malls, indoor buildings and urban canyon in-vehicle environments.All of the tests presented herein were performed using a various commercial state of the art mobile phones which using and having a built-in GPS receiver. In order to calculate and record the TTFF period, we have devel-oped a MIDlet program which was subsequently installed in all of the mobile phones used in the data collection.Figure 6. The results of all tests were collected with theMIDlet program.The developed MIDlet collects and logs information about the user's coordinates, serving base station Cell Identity (CI), total number of satellites that is used to calculate the coordinates. The TTFF was measured rela-tive to the time when the assistance data was received at the mobile terminal. The user interface of the MIDlet program is depicted in Figure 6. [12-13]During the data collection, all positions were calcu-lated independently. In other words, it has no a priori knowledge about GPS time, signal propagation and its current position. The GPS receivers were cold-started during all tests. Before cold tests were performed, the mobile terminal was turned off for a period of between 5-6 hours that resulting a cold start. As stated before, in the cold start mode, the receiver has no acquisition aiding information available; it has no information about the current time, the orbits of the satellites or its current posi-tion. Thus, a complete search is necessary.During the in-vehicle tests, the mobile phones were powered up inside the vehicle and they were placed be-tween the front seats.All of the tests performed for this research were done in static conditions. All tests were performed with no orbital, atmospheric or any other errors.In order to SUPL enabled terminal to get assistance da-ta from server, ‘Assisted GPS’ should be selected as a ‘Positioning Method’, and ‘Positioning Server Address’ must be entered in settings of mobile terminal.SUPL enabled A-GPS allows the mobile terminal to request up to date ephemeris (satellite position) data from the server over a packet data network.Figure 7. The total GPRS packet data and duration time forall assistance dataThe transferred average assistance data is 1.28kB up-load and 3.11kB download, 4.39kB at total as shown in Figure 7. Content of transferred information has ex-plained in section 2.When A-GPS info is received successfully, there should be a list of satellites with very short strength bars as shown in Figure 8a. As satellites are found a hollow black bars will appear with the satellites number beside it. Once the GPS chip "locks" onto the satellites signal the bar turns solid black as shown in Figure 8b.Results for measurements in both SET Based and Inte-grated GPS TTFF and position accuracy for measurement results are shown in Table II for three different environ-ments, which include 200 measurements in total. Meas-ured median position errors and Average TTFF for SET based A-GPS are 34m and 50.5 seconds in urban indoor, 32m and 50.3 seconds in shopping mall 25m and 25.2 seconds in urban inside vehicle. And median position errors and Average TTFF for conventional integrated GPS are 42m and 81 seconds in urban indoor, 45m and 70.3 seconds in shopping mall, 32m and 41.5 seconds in urban inside.TABLE II.AVERAGES OF POSITION ACCURACIES AND TTFF VALUES FOR SET BASED AND INTEGRATED GPS MEASUREMENTS.SET BasedAveragesIntegrated GPSAveragesType ofEnvironment TTFF(secs)PositionError(m)TTFF(secs)PositionError(m) Urban Indoor 50.5 34 81 42Shopping Mall 50.3 32 70.3 45Urban In-Vehicle25.2 25 41.5 32The comparison results of TTFF values for SET and Conventional GPS are shown in Figures [9-11] for three environments.Figure 9. Comparison of TTFF values for SET and Conventional GPSin Urban In-Vehicle environment.Figure 8.a. After SUPL assis-tance, GPS knows which satellitesit should search for.Figure 8.b. Locked satellitesFigure 10. Comparison of TTFF values for SET Based and Conven-tional GPS in Shopping Mall environment.Figure 11. Comparison of TTFF values for SET and Conventional GPSin Urban Indoor environment.Inside the indoor areas, integrated GPS could not com-pute position under 40 seconds. Because GPS interrupted from a tall building and receiving signal is being reflected due to reception block or multi-paths by high-rise apart-ment complex. If the data isn't received in full, the Ephe-meris data collection has to start again at the next cycle. No lock was seen in the indoor areas unless mobile de-vice was placed very near to windows.The field tests show that SUPL enabled A-GPS ap-proach promise much better position accuracy and faster TTFF period than conventional GPS, because SUPL en-abled A-GPS architecture increases the capability of a conventional GPS receiver to acquire and track more sat-ellites, thereby improving observation geometry, and in-crease sensitivity over a conventional GPS architecture. These enhanced capabilities come from knowledge of the satellite position and velocity, the initial receiver position, and time supplied by the assistance server. A-GPS bene-fits include TTFF improvement, higher sensitivity and maximum availability due to the receiver not having to download and decode navigation data from GPS satel-lites. Hence, the receiver can spend more time and proc-essing power tracking the GPS signal.VI.C ONCLUSIONSIn the study, a SUPL enabled A-GPS architecture was developed. The advantages of the developed system were compared with the conventional GPS in terms of the TTFF delay time and location accuracy in actual urban environment field tests. The study environment is se-lected as indoor environment, because according to the results of the statistics, a normal user stays most of the day in indoor environments and needs GPS help in such environments. The impact of initial position estimation on the both TTFF and accuracy of calculated position also investigated.The performance of SUPL has been evaluated with da-ta collected from field measurements in a GSM networkin different geographic environments. The study wasdone with real mobile phones and real field measure-ments in live GSM network.Previous related work in the literature used either a si-mulator environment or used sophisticated GPS devicesin field tests. This paper presents the first study where aSUPL based A-GSP system was developed and tested inthe field using commercial mobile phones with limitedGPS capabilities.Our experimental results indicate that the SUPL isvery effective on TTFF delay and position accuracy formobile positioning in different environments. When theuser to reference point distance decreased less than 2 km,a significant decrease in the TTFF and the accuracy was noticed.Moreover, the developed system has minimal impacton the cellular infrastructure and does not necessitate any modifications to the mobile handsets or base stations.Currently, we are working on techniques to improvethe SUPL enabled A-GPS accuracy by exploiting thenetwork attributes more.A CKNOWLEDGMENTThis work has been fully supported by Vodafone I.T., Research & Development Department, TURKEY.R EFERENCES[1]J.A. Farrel and M. Barth, The Global Positioning System and Iner-tial Navigation. New York:Mc Graw Hill, 1999.[2]J. Burkowski, J. Niemela, J. Lempiainen, “Cellular Location Tech-niques Supporting AGPS Positioning,” Proceedings of IEEE VTC-Fall, vol. 1, pp. 429-433, Sept. 25-28, 2005.[3]S. Singh, “Comparison of Assisted GPS (AGPS) Performanceusing Simulator and Field Tests,” Proceedings of ION GNSS, Sep-tember 26-29, 2006.[4]G. Lachapelle, “GNSS Indoor Location Technologies,” Proceed-ings of ION GNSS, December 6-8, 2004.[5]M.D. Karunanayake, M.E. Cannon and G. Lachapelle, “Analysis ofAssistance Data on AGPS Performance,” Measurement Scienceand Technology, vol. 18, pp. 1908-1916, 2007.[6]T. Hu, G. Lachapelle, R. Klukas, “Controlled GPS Signal Simula-tion for Indoors,” Journal of Navigation, vol. 60, pp.265-280, 2007.[7]M.D. Karunanayake, M.E. Cannon, G. Lachapelle, “Evaluation ofAssisted GPS in Weak Signal Environments Using a HardwareSimulator,” Proceedings of the ION GNSS, Sept. 21-24, 2004.[8]3GPP, “Mobile Station (MS) - Serving Mobile Location Centre(SMLC) Radio Resource LCS Protocol (RRLP),” Release 7, 3GPPTS 44.031 V7.7.0, December 2007.[9]Open Mobile Alliance, “Secure User Plane Location Architecture,”Version 1.0, OMA-AD-SUPL-V1_0-20070615-A, 15 Jun 2007.[10]Open Mobile Alliance, “User Plane Location Protocol,” Version1.0, OMA-TS-SUPL-V1_0,[11]Open Mobile Alliance,“Mobile Location Protocol,” OMA-TS-MLP[12]JSR179: LocationAPIforJ2ME/jsr/detail/179.jsp[13]Java ME Technology APIs & Docs/javame/reference/apis.jsp。
移动代理服务器Mobile Agent Server一、是Mobile Agent Server的简称,是协助企业原有业务系统实现无线应用的接入工具,实现MAS接入后企业原有的业务系统可以方便的实现无线应用,如:OA 系统可以实现手机办公、邮件通知、手机审批等。
1、MAS系统组成和功能:MAS系统包括MAS终端、MAS服务器和MAS管理平台,中国移动通过在集团客户(主要为拥有完备企业信息系统的政府行业用户和企业)内部部署移动代理服务器,为集团客户提供的基于移动终端(包括短信、彩信、GPRS 、WAP、手机客户端等)的信息化应用服务。
通过移动代理服务器将不同的行业用户应用和业务延伸到移动终端。
1.1 MAS服务器组成和功能:MAS服务器的组成:MAS服务器由应用接入适配插件模块、业务调度模块、移动安全接入模块及管理模块组成。
各组成完成的功能:应用接入适配插件模块实现移动应用业务的移动应用接口,通过多种移动通讯方式完成移动办公、移动Email、数据的现场查询、采集、录入、WAP应用等移动应用业务。
业务处理模块对从应用系统接收到的数据信息进行处理,主要功能包括信息处理及路由、用户认证、业务调度、日志处理和QoS控制等。
移动安全接入模块一方面通过移动行业网关提供的接口协议,实现MAS服务器与行业网关的数据通信。
另一方面采用安全加密技术提供短信安全接入、彩信安全接入、GPRS安全接入、WAP安全接入、USSD安全接入、智能终端安全接入功能,通过这种方式实现信息的空中加密传输,为MAS终端提供安全服务。
管理模块完成MAS服务器的自管理和服务,可提供网络管理、认证鉴权在内的接口子模块。
可选用业务导航、路由管理、业务管理、数据管理、应用发布、统计分析、地址本管理、系统配置管理等功能模块。
1.2、MAS管理平台:MAS管理平台运行于移动公司,通过加密IP通道与MAS服务器进行通讯,完成对MAS服务器的管理和控制,具体的管理的内容有配置管理、认证管理、监控管理、故障管理、安全管理、升级维护管理。
CONNECTED PAPRMore breathing room for smarter decisionsThe Future Is Connected Leave the old ways of working in the past, and register a ConnectedManual record keeping (if at all)No mechanism to uncover operational insightsNo ability to glean insights Reactive consumable Digitize asset managementInstant access to valuable data inthe cloudIn-depth understanding ofoperations and worker behaviorfrom dataTurn consumable replenishmentinto a proactive practiceReceive pushnotificationsFilter and battery lifepredictionMonitor and trackbattery healthTHE PAST CONNECTED PAPR TODAYTHE FUTUREHow Effectively Are You Managing Your PAPR Fleet?For most companies, PAPR fleet management is an after-thought. Despite the significant, long-term investment requirement to support a PAPR program, management of the assets and consumables is often an unsophisticated, manual and reactive process.• When will I need to replace batteries?• How do I know who is using what unit?• How do I define an efficient filter change-out schedule? Traditionally, these questions (and others) were difficultto answer. Today, Honeywell is leveraging the power of connectivity, data and software to respond to these challenges and make PAPR programs more productive while reducing the total cost of ownership.Honeywell Industrial Safety9680 Old Bailes Rd. Fort Mill, SC 2970701/19© 2019 Honeywell International Inc.How To Get Your Workforce Connected:gatewayapplication on on yourConnectedtechnology dothe heavy lifting。
移动代理的概念及技术架构移动代理的概念移动代理(Mo bile Ag e n t)是90年代中期刚刚兴起的一种分布式计算模型,目的是使程序的执行尽可能靠近数据,降低网络通讯开销,节省带宽,平衡负载,加快任务的执行,从而提高分布式系统的处理效率。
Agent的研究起源于人工智能领域。
Agent是指模拟人类行为关系、具有一定智能并能够自主运行和提供相应服务的程序。
与现在流行的软件实体(如对象、构件)相比,Agent粒度更大,智能化程序更高。
随着网络技术的发展,可阻让Agent在网络中移动并执行,完成某些功能。
利用资源同处一台主机和网络的优势,处理和使用这些资源,代表用户完成特定的任务,这就是移动代理(Mobile Agent)的基本思想。
移动Agent的概念是20世纪90年代由General Magic公司在其商业系统Telescript中提出来的。
移动Agent是一个能在异构的网络中自主地从一台主机迁移到另一台主机,并与其它Agent或资源交互的程序,实际上它是Agent 技术与分布式技术相结合的产物。
移动Agent是一类特殊的软件Agent,它除了具有软件Agent的基本特性——自治性、响应性、主动性,还具有移动性,即它可以在网络上从一台主机自主地移动到另一台主机,代表用户完成指定的任务。
由于移动Agent可以在异构的软、硬件网络环境中自由移动,因此这种新的计算模式能动态适应变化了的网络环境,有效地降低分布式计算中的网络负载、提高通信效率,并具有很好的安全性和容错能力。
移动Agent与传统的网络计算模式有着本质的区别。
它不同于远程过程调用(RPC),这是因为移动Agent能够不断地从网络中的一个节点移动到另一个节点,而且这种移动是可以根据自身需要进行选择的。
移动Agent也不同于一般的进程迁移,因为一般来说进程迁移不允许进程自己选择什么时候迁移以及迁移到哪里,而移动Agent 却可以在任意时刻进行移动,并且可以移动到它想去的任何地方。
agentverse使用案例
1. 聊天机器人:AgentVerse可用于构建聊天机器人,它可以与用户进行自然语言对话。
该机器人可以被应用于客户服务,帮助解答常见问题,并提供技术支持等。
2. 个人助手:AgentVerse能够帮助用户管理日常任务和提醒,如设置闹钟、记事和定时提醒等。
用户也可以向它询问天气、交通状况和其他实用信息。
3. 语音识别系统:AgentVerse可以用于构建语音识别系统,实现用户语音输入的转换。
这种技术可应用于语音搜索、语音助手和语音识别智能家居设备等。
4. 语音合成系统:AgentVerse可以将文本转化为语音,生成自然流畅的语音输出。
这个功能可以被应用于自动电话回复、有声读物和无障碍设备等。
5. 营销智能助手:AgentVerse可以通过自然语言处理和机器学习技术来分析大量的数据,并预测客户需求和购买行为。
这将帮助企业优化市场营销策略,并提供个性化、精确的推荐服务。
6. 虚拟导游:AgentVerse可以用于构建虚拟导游应用程序,向用户提供有关旅游目的地的信息和建议。
用户可以与AgentVerse进行对话,获取旅行建议、预订酒店和查询当地景点等。
7. 智能家居系统:AgentVerse可以与各种智能家居设备进行集
成,实现智能控制和自动化。
用户可以通过语音对话与AgentVerse交互,控制照明、温度、安全系统等。
总之,AgentVerse可以应用于各种领域,如客户服务、个人助手、语音识别、语音合成、智能营销、导游服务和智能家居等,为用户提供更便捷、智能的体验。
大模型al agent在企业应用中的6种基础类型大模型AI Agent在企业应用中的6种基础类型大模型AI Agent,即大型人工智能代理程序,在当今企业应用中发挥着越来越重要的作用。
它们可以处理复杂的任务、提高工作效率、优化业务流程,从而帮助企业更好地应对竞争和挑战。
在企业应用中,大模型AI Agent通常可以分为以下6种基础类型:1. 语音助手型AI Agent:这种类型的大模型AI Agent可以通过语音指令与用户进行沟通和互动。
它们能够理解自然语言、识别语音指令,并能够执行各种任务,比如回答问题、提供信息、安排会议等。
语音助手型AI Agent可以大大提高用户体验,简化用户操作,提高工作效率。
2. 聊天机器人型AI Agent:聊天机器人型AI Agent是一种能够通过文本消息与用户进行对话的大模型AI Agent。
它们通常被用于客户服务、在线支持、销售等领域,能够回答用户的问题、提供帮助、解决问题。
聊天机器人型AI Agent可以24/7不间断地为用户提供服务,节省人力成本,提高客户满意度。
3. 数据分析型AI Agent:这种类型的大模型AI Agent专注于处理和分析大规模数据,从中提取有用的信息和见解。
数据分析型AI Agent可以帮助企业做出更明智的决策、发现潜在的商机、优化运营流程。
它们通常与数据科学家、分析师等团队成员合作,共同完成数据分析任务。
4. 自动化流程型AI Agent:自动化流程型AI Agent旨在自动化重复、繁琐的工作流程,提高生产效率和工作质量。
它们可以代替人工完成机械性的任务,比如数据录入、文件整理、流程监控等。
自动化流程型AI Agent可以帮助企业节省时间、减少错误率、提高效率。
5. 智能决策型AI Agent:智能决策型AI Agent是一种能够根据数据和规则做出决策的大型人工智能程序。
它们可以分析各种信息、权衡利弊、预测结果,帮助企业管理层做出更加科学、合理的决策。
多Agent 系统研究概述王学通,王 伟,于 蕾,王 理(西安理工大学计算机科学与工程学院 陕西西安 710048)摘 要:Agent 是一个能够感知外界环境并具有自主行为能力的以实现其设计目标的自治系统。
Agent 和多Agent 系统的研究已经成为分布式人工智能(DAI )的一个热点。
阐述了Agent 以及多Agent 系统(MAS )的基本概念;多Agent 系统的反应式结构、慎思式结构以及混合式结构等3种基本的体系结构与多Agent 系统的BDI 模型,以及多Agent 系统中的通信、协调、协商、和合作等关键的技术问题。
最后给出了多Agent 系统研究尚需要解决的一些问题。
关键词:分布式人工智能;Agent ;MAS ;结构;模型中图分类号:TP18 文献标识码:B 文章编号:1004373X (2006)1006503Summary on R esearch of Multi Agent SystemWAN G Xuetong ,WAN G Wei ,YU Lei ,WAN G Li(School of Computer Science &Engineering ,Xi ′an University of Technology ,Xi ′an ,710048,China )Abstract :Agent is a system that can be viewed as perceiving its environment through sensors and acting upon that envi 2ronment through effectors.Researches on Agent and MultiAgent System (MAS )have became the hotspot in the field of Dis 2tributed Artificial Intelligence (DA I ).This paper presents the basic concept of Agent and Multi Agent System.it also intro 2duces the architecture of system and the BDI model of MAS.Finally ,it gives us some key technical problems which includecommunication ,coordination and cooperation.K eywords :distributed artificial intelligence ;Agent ;MAS ;architecture ;model收稿日期:200511101 引 言随着计算机技术和信息科学技术的快速发展,计算环境发生了很大的变化。
Robots,while incredibly useful in many aspects of modern life,do come with a set of drawbacks that should be considered when integrating them into various systems and daily routines.ck of Emotional Intelligence:Unlike humans,robots do not possess the ability to understand or respond to emotions.This can lead to a lack of empathy and understanding in situations where emotional intelligence is crucial,such as in healthcare or customer service.2.High Initial Costs:The development,production,and maintenance of robots can be expensive.This high cost can be a barrier for many businesses and individuals,especially when considering the potential return on investment.3.Job Displacement:The increasing use of robots in the workforce can lead to job displacement for humans.This is particularly concerning for lowskilled laborers who may find it difficult to retrain for new jobs in a rapidly evolving job market.4.Dependency on Technology:Overreliance on robots can lead to a loss of human skills and abilities.For example,if robots are used to perform repetitive tasks,humans may lose the dexterity and cognitive skills associated with those tasks.5.Ethical Concerns:The use of robots raises several ethical questions,such as the rights of robots,the potential for misuse in surveillance,and the implications of creating machines that can mimic human behavior.6.Limited Creativity:Robots are programmed to perform specific tasks and follow algorithms.They lack the ability to think creatively or solve problems in ways that are not preprogrammed,which can be a limitation in dynamic and unpredictable environments.7.Technical Failures:Robots,like any technology,can malfunction or fail.This can lead to significant problems,especially in critical applications such as healthcare or transportation,where a robots failure could have serious consequences.8.Security Vulnerabilities:Robots that are connected to networks can be vulnerable to hacking and cyberattacks.This can compromise the safety and security of the systems they operate within.ck of Adaptability:Robots may struggle to adapt to new or unexpected situations. This inflexibility can be a significant drawback in environments that require quickthinking and adaptability.10.Social Isolation:The increased use of robots in social settings can lead to social isolation,as human interaction is reduced.This can have negative effects on mental health and social skills development,especially among children and the elderly. Understanding these potential drawbacks is essential for responsible and ethical use of robotics technology.It is crucial to balance the benefits of automation with the potential risks and challenges to ensure a harmonious integration of robots into society.。
通过替换方法实现的AgentBuilder
本文介绍了一种使用替换方法实现的AgentBuilder,旨在为计算机图形学、游戏开发和机器人控制系统等领域提供一种新的构建智能代理的方法。
替换方法是一种常用的数据结构操作,可用于快速替换数组或列表中的特定元素。
通过使用替换方法,我们可以实现高效地构建智能代理,从而提高计算机图形学、游戏开发和机器人控制系统等领域的应用性能。
AgentBuilder是一种用于构建智能代理的框架,它提供了许多内置的代理类和组件,如感知器、控制器和动作生成器等。
这些组件可用于实现各种不同的智能代理,如机器人、游戏角色和虚拟场景中的NPC等。
通过替换方法实现的AgentBuilder,可以在构建代理时更加灵活和高效。
我们可以使用替换方法快速替换代理中的组件和参数,从而实现对代理行为的快速修改和定制。
此外,替换方法还可以帮助我们避免在代码中重复编写相同的逻辑,从而提高代码的可读性和可维护性。
总之,通过替换方法实现的AgentBuilder是一种高效、灵活和易于使用的构建智能代理的方法。
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ai agent 指标
AI Agent的指标可以包括以下几个方面:
1.准确度:AI Agent的预测、分类或决策的准确率。
这是衡量AI Agent性能的重要指标。
2.效率:AI Agent完成特定任务所需要的时间和资源。
效率的提高意味着更高的处理速度和更低的资源消耗。
3.可靠性:AI Agent在面对相似的输入时,能够产生一致的输出。
这是衡量AI Agent稳定性和可靠性的重要指标。
4.解释性:AI Agent能够提供其决策或预测的合理解释。
这是衡量AI Agent的可理解和可信任程度的重要指标。
5.创新性:AI Agent能够产生新颖和有创意的建议或解决方案。
这是衡量AI Agent在解决问题和应对新挑战方面的能力的重要指标。
6.可扩展性:AI Agent的性能在面对大规模数据或任务时,仍然能够保持稳定和高效。
这是衡量AI Agent可扩展性和适应性的重要指标。
7.可解释性:AI Agent的内部工作原理和决策过程可以被人类理解。
这是衡量AI Agent透明度和可信任程度的重要指标。
8.用户满意度:AI Agent提供的服务或建议得到了用户的认可和满意。
这是衡量AI Agent对用户需求和期望满足程度的重要指标。
这些指标可以根据具体的任务和需求进行选择和调整,以全面评估AI Agent的性能和表现。
Mobile Agent Interoperability RevisitedV olker Roth,Ulrich Pinsdorf,and Walter BinderFraunhofer Institut f¨u r Graphische DatenverarbeitungRundeturmstraße6,64283Darmstadt,Germany{vroth|ulrich.pinsdorf}@igd.fhg.deCoCo Software Engineering GmbHMargaretenstraße22/9,A-1040Wien,Austriaw.binder@coco.co.atA major setback for mobile agent technology is–apart from a frequently cited absence of appropriate security mechanisms–a lack of interoperability between systems for mobile agents,which prevents mobile agents from reaching“critical mass”for widespread application.Interoperability is required where systems of different vendors come into contact with each other.More precisely, two mobile agent systems are interoperable if a mobile agent of one system can migrate to the second system,the agent can interact and communicate with other agents on this system(or even remote agents), the agent can leave this system,and it can resume its execution on the next interoperable system.At the time of writing,we are aware of only one attempt to provide means of interoperability among systems of mobile agents,which is the dated MASIF proposal[1].FIPA is also active in the standardization of agent mobility1is-sues,but this particular thread of FIPA’s work focuses on a high level of ab-straction,and,to the best of our knowledge,the document did not have much public scrutiny yet.It is therefore fair to say that these existing standardiza-tion efforts have not yet shown to be effective to provide actual interoperability among systems for mobile agents with regard to our definition.Rather than following the top down approach to interoperability by means of standards,we chose to take a bottom up approach based on voluntary and practical interoperability with other systems for mobile agents.In this vein, a working group was established in the Special Interest Group on Intelligent and Mobile Agents,which is part of AgentLink,2Europe’s Network of Excel-lence for Agent-Based Computing.Current members of this working group are CoCo Software Engineering GmbH,Austria,Fraunhofer Institute for Computer Graphics,IKV++,and University of Jena,Germany.The short-term goals of this working group are threefold:1.The exploration and demonstration of practical interoperability within a dis-tributed mobile agent testbed of multiple heterogeneous agencies.2.The design of harmonized interfaces for the purpose of mobile agent invo-cation,migration target specification,and actuation of migration.3.The design of patterns that facilitate adaption of mobile agents of heteroge-neous agent systems in a given system.The expected outcome is a working interoperability layer for the mobile agent systems enago Mobile,J-SEAL2,SeMoA,and Tracy that can serve as a role model for the integration of heterogeneous systems.The long-term goals include the design of a unified and open architecture that allows to plug in modules that represent the individual strengths of the working group members,as well as non-affiliated contributions.From a layering perspective,we target a micro--kernel architecture that allows to insert e.g.,layers between the JVM and the agent system that improve the security of the JVM against malicious code.Current achievements include the design of an abstraction layer for SeMoA3 that we call a Lifecycle pattern,and that is closely related to the Factory pat-tern[2].This pattern has been applied successfully to the Jade[3]and Tracy[4] systems,whose agents run seamlessly in SeMoA and may benefit transparently from the mobility and security features provided by SeMoA[5].We chose these platforms because each stands for a major topic in mobile agent interoperabil-ity.Jade is known for its focus on FIPA compliant agent communication,Tracy concentrates on efficient migration.Instances of the Lifecycle pattern provide agents a view on SeMoA that mimicks the view they have on their native system.More precisely,lifecycle instances fullfill two tasks.First,they translate between the native SeMoA life-cycle and the lifecycle of the emulated system.Second,they act as hooks into the acme4Agent setup routines,called e.g.after migration,typically involve an initialization of the agent with an interface class which provides access to the agent system.Agents wrapped by a specific lifecycle can use their native API for commu-nication,migration,and interaction with the system without recompilation of their code.Furthermore,the lifecycle pattern provides the possibility to observe and control the agent’s access to system information according to the security policy of the hosting system–in our case the SeMoA system.Adaption of agent communication has two specific problems:enabling the lifecycle to access the acme communication infrastructure and the correct adressing of peer agents.The adaption of acme communication interfaces turnedout to be easier as expected.For the Jade system,which communicates by means of the IIOP protocol[6],we built a message service which acts as IIOP stub and is globally accessible for Jade lifecycles.Outgoing messages will be hand over from the lifecycle to the message service which simply drops them into the IIOP channel.The other way around,incoming messages will be dispatched to the particular lifecycle of the receiver agent.The adaption for Tracy’s commu-nication infrastructure was quite similiar.Tracy uses the meeting metapher for communication and posts messages on a system global blackboard.We wrapped a blackboard instance in a globally accessible service which will be used by all Tracy lifecycles on the host.The adaption of various communication channels has the drawback that we run multiple communication channels concurrently. We hope to address this problem in the future with a concept for interoperable integration of multiple communication infrastructures.The correct addressing of peer agents is less troublesome for acme agents that are created on a SeMoA server.Many agent systems use naming schemes based on the Uniform Resource Locator[7]syntax,for instance something like wombat@:40000/strangeplace,where“wombat”is a name that can be chosen freely by the agent’s creator.However,SeMoA allows no free choice of an agent’s name,instead an agent’s name is computed im-plictly5from a digital signature of its static part(see[9]for reference).If the agent is created on the SeMoA server,and its implicit name is computed as f42a1cc0then the agent can be given the name f42a1cc0@: 40000/strangeplace in order to match acme’s syntax.A suitable mapping mechanism must be used by the lifecycle implementation in order to translate back and forth between these names as required.Our experience up to the time of writing shows that agent communication is less of a problem when compared to agent migration,though.Migration is often more tightly interwoven in a system’s design and implementation.For instance,SeMoA’s security policy requires that migration is initiated only after all threads of the migrating agent have terminated,Tracy agents for instance have to throw a particular exception at any time during their execution in order to initiate migration.Nevertheless migration was realised for Tracy agents;6they are able to migrate back and forth between SeMoA servers.The next step is to implement a gateway which allows interoperability with the transport protocol of Tracy and therefore migration to and from a native Tracy system,too.The lessons we learned so far fall into two broad categories.First,we gained insight into design patterns that help to build agent systems in a way that facil-itates provision of interoperability.Second,we gained insight in designs that inhibit provision of interoperability.We concentrate on agent setup,lifecycle, and system interfaces.AcknowledgementsWe thank Peter Braun and Jan Eismann from the University of Jena,Germany, for kindly providing access to the source code of Tracy.References1. ojicic,M.Breugst,I.Busse,J.Campbell,S.Covaci,B.Friedman,K.Kosaka,nge,K.Omo,M.Oshima,C.Tham,S.Virdhagriswaran,and J.White,“MASIF–The OMG Mobile Agent System Interoperability Facility,”in Proceedings of the Second International Workshop on Mobile Agents(MA’98)(K.Rothermel and F.Hohl,eds.),vol.1477of Lec-ture Notes in Computer Science,pp.50–67,Berlin Heidelberg:Springer Verlag,September 1998.The MASIF specification is available from URL:http://www.fokus.gmd.de/ research/cc/ecco/masif/doc/97-10-05.pdf.2. 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