A Mobile-Floating Agent Scheme for Wireless Distributed Computing

Transcription

1 1995 IEEE, to appear in the proceedings of PIMRC 95, Toronto, Cannda. A -Floating Agent Scheme for Wireless Distributed Computing George Y. Liu, A. Danne, A. Marlevi and G. Q. Maguire Jr.* System Research Department, Ericsson Radio Systems AB S Stockholm, Sweden <eraliu@era-t.ericsson.se> *Department of Teleinformatics, Royal Institute of Technology S Stockholm, Sweden Abstract This paper presents a novel -Floating (MF) agent scheme for supporting global distributed mobile computing. The principal contribution of this paper is to innovatively apply virtual memory concepts to mobile systems by deploying MF-agents to decouple service and resource from the underlying network and move around following or proceeding their mobile users. The MF-agents maintain data structures associated with a mobile user. By combining the mobile-floating agent functionality with a predictive mobility management algorithm, services and user data may be pre-connected and pre-assigned at the locations or cells to which the user is moving. Thus, the user can immediately receive services or maintain their data structures with the same efficiency as at the previous location. I. INTRODUCTION With the development of the digital wireless networks and portable computers, mobile distributed computing will be a new dimension for future mobile communication systems. The emergence of wireless distributed computing has an impact on both the fixed computing environment, where the computing equipment are assumed to have a fixed position in the network, and the traditional wireless mobile networks. Mobility of computers introduces challenging new problems that were not encountered in the design and implementation of conventional mobile networks, nor in fixed computer networks. computer users need to access a mix of network based resources, such as files, database, etc., while mobile. Although the current mobile cellular networks support user/ terminal mobility, they were mainly designed with connection oriented voice communication in minds. On the other hand, traditional computer networks and applications are based on the assumptions that the configuration of the system is relatively static and network communication is homogeneous with relatively high bandwidth and low latency. Although today it is possible to connect a portable computer to a fixed network through a cellular modem or a wireless LAN, it is not efficient for wireless data access in that it does not support data and service mobility. While users and terminals are mobile, data about them and the location of the data they wish to access is still primarily configured statically in the system. Therefore, the mobility of users/terminals and the constraints of wireless links require innovative schemes or applications which can adapt to weak-link access while exploiting location-dependent or location-aware information to provide transparent mobility. How to efficiently provide mobile data access and dynamically cope with the mobile nature of mobile users by providing service and resource mobility and intelligent service preconnection and resource pre-arrangement are the questions addressed in this paper. Previous proposals for supporting wireless computing include IP[1 5 8], packet data over mobile radio channels[2] and network layer host migration[12]. These mainly address the network or lower layer mobility issues. Although these proposals make it possible for a mobile computer to access data through mobile networks, they provide only very primitive mechanisms for supporting mobile computing. Thus there remain several problems, such as serial bottleneck, TCP timer backoff[1] and unacceptably long pauses in communications during handover[7], which result in performance degradation. The I-TCP proposed by A. Bakre, et al.[13] addresses some of the transport layer problems by using an indirect transport layer protocol for mobile hosts. Although providing a means of supporting host mobility, it restricts itself to the transport layer and lacks location-aware information and mobility-aware application support, and thus inadequately supports all the mobility features required. In this paper, we present a mobile application programming interface (mobile-api) with mobile-floating agents to support wireless distributed computing. The principal contribution of this paper is to apply virtual memory concepts to mobile systems by deploying mobile-floating agents who decouple services and resources from the underlying network (allowing them to move around following their mobile users). By combining mobile-floating agent with a predictive mobility management scheme, services and resources can be preconnected and pre-arranged at the location to which the user is moving. The rest of this paper is divided into the following sections: section 2 describes the Distributed System Platform with mobile-api, section 3 proposes mobile-floating agent concepts, and section 4 presents performance evaluation. II. MOBILE DISTRIBUTED SYSTEM PLATFORM & MOBILE-API A. Our Computing Model Computing and communications are becoming inseparable synergistic activities independent of time and location, i.e., with mobility. Therefore, we view mobile computing as the PIMRC 95 Page: 1(5)

2 combination of three important and interrelated properties: Computation, Communication and Mobility, as shown in Figure 1. Figure 1. A view of mobile computing and its important components Computation includes the computing devices with their dramatically increasing processing power. Today, notebook computers provide essentially the same processing power as desktop workstations. Communication systems include the different wireless and wired networks and span a wide range of bandwidths, ranging from ~1 Kb/s for macrocells and up to 2-1 Mb/s for indoor picocells. Mobility is an aspect of user behavior. The concepts of mobility management have been used in cellular mobile networks (designed for supporting mobile voice communication) for many years. However, adapting mobility management to mobile computing, to provide efficient service and resource mobility management, remains to be done. B. Distributed-System Platform with -API To cope with the varying bandwidth and connectivity of different links at different locations and to efficiently support service and resource mobility, the Distributed System Platform (MDSP) with -Floating (MF) Agents is proposed. Figure 2 shows the relationship of the MDSP and 1Mb/s Mobility Computing Computation Applications MINT Interface (-IP) Communication Applic. Programming Interface(API) Low Layers IR Radio GSM Mobitex 2Mb/s... MF_Agent Networks 9.6Kb/s 8 Kb/s Figure 2. An MD Platform with Floating Agent Supports Applications applications in a mobile multi-link environment, where there may co-exist different networks, e.g., Mobitex s 8 kb/s link for a wide coverage area, an indoor infrared (IR) link at up to 1 Mb/s, etc. At the lower layers, the MINT ( INTernet router)[1 2] provides different hardware interfaces The -IP [1 5 8] protocol is used to support host mobility. At the higher layers, the MINT software provides a common mobile distributed platform with MF-agents supporting mobile applications. The MDSP consists of Location-Sensitive Information Management (LSIM) functions and Predictive Mobility Management (PMM) functions. On top of MDSP, additional functions (shown in Figure 3) support applications: mobile-distributed file systems, mobile distributed databases, etc. File Manager with LCPM Database Manager with PCP Figure 3. An example of an MDSP Model. LCPM: Location-dependent Caching and Prefetching Management. PCP: Page Caching and Prefetching Functions A summary of the different parts of the MDSP follows: The LSIM in the MDSP manages location-sensitive information and maps it to the services offered by the mobile infrastructure at specific geographical locations. It is also responsible for informing both the applications and their supporting agents of location changes and providing dynamic service connections. The Predictive Mobility Management functions consist of: Location Prediction Functions (LPF) and Floating Agent Assignment functions (FAA), which assigns the floating agent to different locations according to the location prediction and provides service pre-connection and service/resource mobility. Location prediction can be performed automatically, by a mobile motion prediction algorithm[1], or manually, for example via a user s calendar. The LSIM functions and the mobile file system manager with LCPM as well as the LPF have been described in our previous papers[6 9]. Thus, this paper will focus on the Floating Agent Assignment functions. III. MOBILE FLOATING AGENTS A. Floating Agent Concepts Windows applic. support Distributed System Platform Location-Sensitive Information Management Functions (LSIM) Other applications Predictive Mobility Managemet Functions (PMM) In order to distribute network services and resources closer to mobile users, i.e., to provide service and resource mobility in wireless data networks, we introduce the concepts of - Floating Agents (MF-agent) and Mobility Agents (M-agent). An MF-agent is a software entity which consists of a set of processes, executing on remote fixed hosts or mobile support routers(msr)[5], that can communicate and connect with the local host resources and manage a variable replicated secondary data cache on behalf of an M-agent. An M-agent is a software entity which consists of a set of processes, executing on a home fixed host or router, that communicates with and PIMRC 95 Page: 2(5)

3 pre-assigns an MF-agent to remote fixed hosts or routers on behalf of a mobile user. With the support of the M-agent and MF-agent, service logic and resources are not bound to the underlying network and are thus free to follow the mobile users. By using predictive mobility management[9 1], the MF-agent pre-connects services, pre-arranges the secondary cache and prefetches data to where it expects the user is going (see Figure 4), just as a travel agency pre-arranges a hotel room or other services for the user when travelling. Location 1 Location 2 Network IP Layer Terminal Services/ Resources M-Agent MDSP-base Home-Agent PMM Server Forward Prediction Variable Data Consistency _REG_INFO Pre-assignment FA_REG_REPLY FA_REG_REQ Services/ Server 2nd Resources Cache Service Pre-connection rlogin MF-Agent MDSP-base Foreign-Agent Visiter MH_REG_REQ MH_REG_ REPLY Location PMM Terminal Network location 1 Access Networks Services FAA M-Agent User Data Cache(2nd) Prediction Pre-assignment Pre-arrangement Backbone Network Figure 4. M-agent and MF-agent support service pre-connection and resource pre-arrangement. B. Floating Agent Protocol MF-Agent The MF-agent is assumed to have basic mobility support from the network layer, via a protocol such as -IP [5], IP mobility support[8] or network layer host migration transparency[12]. The MF-agent pre-assignment protocol is depicted in Figure 5. The MDSP-base, which represents the MDSP in the network, provides a common base which supports MF-agent migration. The M-agent is a representative of the user in a network and is responsible for creating, deleting and managing the MF-agents on behalf of the mobile user. Only an M-agent can assign MF-agents. An MF-agent acts as an M-agent (AMagent) when it s user is collocated and registered with the active MF-agent. The M-agent at the home location will always be an M-agent and is responsible for control of all communication sessions and maintains Variable Data Consistency[11] between the home resources (data/files) and its pre-assigned MF-agents or its AM-agent on behalf of its user. The life time of an MF-agent is dependent on the following criteria: Timer parameter (t mf ): Each MF-agent maintains a timer which is set when the MF-agent is assigned. This timer is re-set when the MF-agent is acting as an AM-agent. LRU parameter (l mf ): Each MF-agent maintains a LRU parameter which is set when the MF-agent is assigned. The LRU parameter provides a priority FAA 2nd Cache Network location 2 Services Fixed Network Data Data infrastructure Data Data Nodes Figure 5. Floating Agent Protocol index for shared resources (e.g., disk space for secondary cache, memory, etc.) with other MF-agents on the same node. If the resources have to be reclaimed, the MF-agent(s) with the highest LRU parameter is chosen as a victim(s). An MF-agent pre-assignment process involves the exchange of 2 messages: 1) MF_ASSIGNMENT_REQ: The mobile terminal sends an MF_ASSIGNMENT_REQ to its M-agent or AM-agent in the local network with the address of the new location. The M-agent registers the request and forwards it to the remote MDSP-base. 2) MF_ASSIGNMENT_REPLY: On receiving the MF_ASSIGNMENT_REQ message, the remote MDSP-base creates an MF-agent, if it can provide service; the MF-agent presents itself to the Foreign Agent (FA)[8] and asks to be registered; and then, sends an MF_ASSIGNMENT-REPLY back to the M- agent. The M-agent maintains a variable data consistency link with the MF-agent and its secondary (2nd) cache and passes the reply back to the mobile. Otherwise the MDSP-base sends the a reply denying service. At the new location, the mobile terminal registers as follows: 1) The Terminal sends a Registration Request to the prospective FA to begin the registration process (as described in [8]). 2) If there is an MF-agent registered for the user, the FA sends a reply to the mobile terminal to confirm its request and passes a link to the MF-agent. Otherwise, the conventional 4-step registration processes[8] should be followed. C. MF-agent Assignment Algorithm Consider an area covered by cells with each cell serviced by an MSR. Let λ be the average move rate which is defined by the average number of new MSRs which have been passed per unit time, and let m be the mobility density factor during τ m. The m is defined as the average number of new MSRs which PIMRC 95 Page: 3(5)

4 A d1 A: m*t C 1 = c 11 + c 12 m*τ m B m*τ m d2 MA τ c2 C 2 = c 21 + c 22 MFA τ c3 C 3 MFA d s < 1 s = 1 s > 1 Figure 6. An example of service distance and service rate s. have been passed during time τ m. Let s denote service rate which is defined by the number of MF-agents that service each unit movement of the mobile users, that is: d s = h m τ m where d is the service distance, h is a hierarchic factor defined by the total number of MSRs under the MF-agent, τ m is a period of time in which the m is sampled. To ensure that there is at least one MF-agent supporting each user whenever the user moves, the service rate should be s 1, that is, d hmτ m. The MF-agent assignment algorithm 1 (without any movement prediction[1]) is: 1) Calculate the mobility factor m during each τ m ; 2) Define a circle centered at the current location with a radius d = int( h m τ ) and assign MFAs within m the circle; 3) If at the boundary of the circle, repeat from step 1. IV. PERFORMANCE EVALUATION The MF-agent architecture discussed above can be summarized in the following MF-agent model, as shown in Figure 7A. Let C 1 denote the cost (load and delay per unit bandwidth) of sending a message between a mobile terminal () and its M-agent (MA) or MF-agent (MFA), C 2 between an MA and its MFA and C 3 between its two MFAs respectively. C 1, C 2 and C 3 can be subdivided into on-line costs (mainly delay): c 11, c 21 and c 31, and background costs (fixed system load): c 12, c 22 and c 32. The cost matrix is shown in Figure 7B. A. Assumptions To analyze the performance gain without loss of generality, Let assume that the total number of MSRs is N (N >> mτ m ) and τ m >> τ c3, where τ c3 is the time unit of sending a message between two MFAs. We also assume that the time intervals of 1. For details of the predictive assignment algorithms, the reader is referred to [1] and [14]. B: Figure 7. The MF-agent Model the movement between consecutive MSRs follows a Poisson distribution with λ = m and the LRU parameter associated with each MFA having an exponential distribution, i.e., l mf = e t. It is also assumed that the mobile user is initially at home, when m =. In carrying out the simulation, it is also assumed that the online costs are twice as significant as the background costs and as well as for the wireless and wired cases. The cache miss rate[6] is assumed to be 1%. N = 1, T = 1 minutes. B. Results and Discussion The Cost Matrix on-line background Wireless C 1 c 11 c 12 Wired C 2 c 21 c 22 Wired C 3 c 31 c 32 Figure 8 shows the normalized simulation results of the Read&Write Operation Delay (normalized) Fixed System Load (normalized) With MFAs Without MFAs _._._. N distributed With MFAs Without MFAs _._._. N distributed Figure 8. The Delay and Load of a read and write operation in a system with, without MFAs and with N-distribution PIMRC 95 Page: 4(5)

5 distributed MFA assignment algorithm comparing with the system without MFAs and the system with N-distribution. It can be seen that the delay of a read & write operation in a system with MFAs is reduced by more than 3% within the mobility density interval [.2, 1], while the fixed system load is increased due to the mobility of MFAs, due to the service/ resource mobility overhead. There is a trade-off between the latency and load on a fixed system. When a user, for example, is at home network during τ m, i.e., the mobility density m =, the system with MFAs will be the same as the system without MFAs because d = int( m τ ) =. As the mobility density m increases, the delay of read & write operations with MFAs are reduced comparing with that without MFAs, but the background (fixed) network load will increase due to the increased d, resulting in fixed load c 32 increasing, e.g., at m =.5, the fixed network load of the system with MFAs is twice as much as that without MFAs. When d = (N/π) 1/2, i.e., at m 1, the fixed network load will be more than that of an N- distributed system due to mobility and the total performance gain is diminishing, as shown in Figure 9. Therefore, the MFA assignment algorithm discussed above is more suitable for low or medium mobility users. The total performance gain is over 2% in the mobility density interval [.15,.65]. For high Performance Gain (1%) Figure The Performance Gain with MFAs mobility users, a predictive mobility management algorithm [1] is necessary in order to reduce mobile-floating agents assignment overhead and provide better performance. The mobile-floating agents are not necessarily assigned to the area within radius-d, as described in the above algorithm, but to the area according to the user s movement pattern [1][14]. Although the MFA scheme is primarily designed for supporting mobile computing, it can also be used to build a mobile distributed Home Location Register (HLR) in PCS networks to reduce the call set up time. V. CONCLUSION We have proposed a mobile distributed-system platform with mobile-floating agents to support wireless distributed computing. The concept of mobile-floating agents is proposed to decouple service and resources from the underlying network and support service and resource mobility. We have also proposed a simple MFA assignment algorithm. Simulation shows that for medium mobility density users, this algorithm improves the performance of read & write operations by more than 2%. For a read only operation, this scheme provides virtually the same efficiency as at home location. Since a high proportion (about 2/3) of computing operations are read, such as database access, etc., this scheme with the radius-d assignment algorithm can improve overall user performance by about 3%. ACKNOWLEDGMENTS We would like to thank Prof. Björn Perhson, Prof. Jens Zander, Dr. Frank Reichert, Dr. Håkan Ericsson and Miss Hong Rehn for helpful discussions and their support of this work. REFERENCES [1] D. Duchamp, S. K. Feiner and G. Q. Maguire Jr., Software Technology for Wireless Computing, IEEE Network Magazine, Nov [2] C. K. Siew and David J. Goodman, Packet data transmission over mobile radio channels, IEEE transactions on vehicular technology, Vol. 38, No 2, May 1989, pp [3] B.R. Badrinath, A. Arup and T.Imielinski, Structuring Distributed Algorithms for Hosts, Technical Report, Department of Computer Science, Rutgers University, June, [4] R. Hager, A Klemet, G. Q. Maguire Jr., M.T.Smith, and Frank Reichert, MINT - A Internet Router, Proceedings of the IEEE Vehicular Technology Conference 93, Institute of Electrical and Electronics Engineers, May 18-2, [5] J. Ioannidis and G. Q. 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