Ben Liang

Predictive distance-based mobility management for PCS networks

This paper presents a mobile tracking scheme that exploits the predictability of user mobility patterns in wireless PCS networks. Instead of the constant velocity fluid-flow or the random-walk mobility model, a more realistic Gauss-Markov model is introduced, where a mobiles velocity is correlated in time to a various degree. Based on the Gauss-Markov model, a mobiles future location is predicted by the network based on the information gathered from the mobiles last report of location and velocity. When a call is made, the network pages the destination mobile at and around the predicted location of the mobile and in the order of descending probability until the mobile is found. A mobile shares the same prediction information with the network and reports its new location whenever it reaches some threshold distance away from the predicted location. We describe an analytical framework to evaluate the cost of mobility management for the proposed predictive distance-based scheme. We then compare this cost against that of the regular, non-predictive distance-based scheme, which is obtained through simulations. Performance advantage of the proposed scheme is demonstrated under various mobility and call patterns, update cost, page cost, and frequencies of mobile location inspections.

Predictive distance-based mobility management for multidimensional PCS networks

This paper presents a mobile tracking scheme that exploits the predictability of user mobility patterns in wireless PCS networks. In this scheme, a mobiles future location is predicted by the network, based on the information gathered from the mobiles recent report of location and velocity. When a call is made, the network pages the destination mobile around the predicted location. A mobile makes the same location prediction as the network does; it inspects its own location periodically and reports the new location when the distance between the predicted and the actual locations exceeds a threshold. To more realistically represent the various degrees of velocity correlation in time, a Gauss-Markov mobility model is used. For practical systems where the mobility pattern varies over time, we propose a dynamic Gauss-Markov parameter estimator that provides the mobility parameters to the prediction algorithm.Based on the Gauss-Markov model, we describe an analytical framework to evaluate the cost of mobility management for the proposed scheme. We also present an approximation method that reduces the computational complexity of the cost evaluation for multidimensional systems. We then compare the cost of predictive mobility management against that of the regular, nonpredictive distance-based scheme, for both the case with ideal Gauss-Markov mobility pattern and the case with time-varying mobility pattern.The performance advantage of the proposed scheme is demonstrated under various mobility patterns, call patterns, location inspection cost, location updating cost, mobile paging cost, and frequencies of mobile location inspections. As a point of reference, prediction can reduce the mobility management cost by more than 50% for all systems, where a the mobile users have moderate mean velocity and where performing a single location update is as least as expensive as paging a mobile in one cell.

Ad Hoc mobility management with uniform quorum systems

A distributed mobility management scheme using a class of uniform quorum systems (UQS) is proposed for ad hoc networks. In the proposed scheme, location databases are stored in the network nodes themselves, which form a self-organizing virtual backbone within the flat network structure. The databases are dynamically organized into quorums, every two of which intersect at a constant number of databases. Upon location update or call arrival, a mobiles location information is written to or read from all the databases of a quorum, chosen in a nondeterministic manner. Compared with a conventional scheme [such as the use of home location register (HLR)] with fixed associations, this scheme is more suitable for ad hoc networks, where the connectivity of the nodes with the rest of the network can be intermittent and sporadic and the databases are relatively unstable. We introduce UQS, where the size of the quorum intersection is a design parameter that can be tuned to adapt to the traffic and mobility patterns of the network nodes. We propose the construction of UQS through the balanced incomplete block designs. The average cost, due to call loss and location updates using such systems, is analyzed in the presence of database disconnections. Based on the average cost, we investigate the tradeoff between the system reliability and the cost of location updates in the UQS scheme. The problem of optimizing the quorum size under different network traffic and mobility patterns is treated numerically. A dynamic and distributed HLR scheme, as a limiting case of the UQS, is also analyzed and shown to be suboptimal in general. It is also shown that partitioning of the network is sometimes necessary to reduce the cost of mobility management.

Virtual backbone generation and maintenance in ad hoc network mobility management

In this paper, we present the implementation issues of a virtual backbone that supports the operations of the uniform quorum system (UQS) and the randomized database group (RDG) mobility management schemes in an ad hoc network. The virtual backbone comprises nodes that are dynamically selected to contain databases that store the location information of the network nodes. Together with the UQS and RDG schemes, the virtual backbone allows both dynamic database residence and dynamic database access, which provide high degree of location data availability and reliability. We introduce a distributed database coverage heuristic (DDCH), which is equivalent to the centralized greedy algorithm for virtual backbone generation, but only requires local information exchange and local computation. We show how DDCH can be employed to dynamically maintain the structure of the virtual backbone, along with database merging, as the network topology changes. We also provide a means to maintain connectivity among the virtual backbone nodes. We discuss optimization issues of DDCH through simulations. Simulation results suggest that the cost of ad hoc mobility management with a virtual backbone can be far below that of the conventional link-state routing.

Signal threshold adaptation for vertical handoff in heterogeneous wireless networks

The convergence of heterogeneous wireless access technologies has been envisioned to characterize the next generation wireless networks. In such converged systems, the seamless and efficient handoff between different access technologies (vertical handoff) is essential and remains a challenging problem. The heterogeneous co-existence of access technologies with largely different characteristics results in handoff asymmetry that differs from the traditional intra-network handoff (horizontal handoff) problem. In the case where one network is preferred, the vertical handoff decision should be carefully executed, based on the wireless channel state, network layer characteristics, as well as application requirements. In this paper, we study the performance of vertical handoff using the integration of 3G cellular and wireless local area networks as an example. In particular, we investigate the effect of an application-based signal strength threshold on an adaptive preferred-network lifetime-based handoff strategy, in terms of the signalling load, available bandwidth, and packet delay for an inter-network roaming mobile. We present an analytical framework to evaluate the converged system performance, which is validated by computer simulation. We show how the proposed analytical model can be used to provide design guidelines for the optimization of vertical handoff in the next generation integrated wireless networks.

Tuning the carrier sensing range of IEEE 802.11 MAC

We investigate the effects of the carrier sensing range of the IEEE 802.11 multiple access control (MAC) scheme in this paper. Contrary to the simple and inaccurate cut-off circular collision model that is commonly used, we employ a more accurate collision model to realistically simulate MAC schemes in ad hoc networks. We argue that the carrier sensing range is a tunable parameter that can significantly affect the MAC performance in multihop ad hoc networks. An optimal carrier sensing range should balance the trade-off between the amount of spatial frequency reuse and the possibility of packet collisions. A reward formulation for the optimization of the carrier sensing range is presented. Extensive simulation results are provided to substantiate our study.

Data Persistence in Large-Scale Sensor Networks with Decentralized Fountain Codes

It may not be feasible for sensor networks monitoring nature and inaccessible geographical regions to include powered sinks with Internet connections. We consider the scenario where sinks are not present in large-scale sensor networks, and unreliable sensors have to collectively resort to storing sensed data over time on themselves. At a time of convenience, such cached data from a small subset of live sensors may be collected by a centralized (possibly mobile) collector. In this paper, we propose a decentralized algorithm using fountain codes to guarantee the persistence and reliability of cached data on unreliable sensors. With fountain codes, the collector is able to recover all data as long as a sufficient number of sensors are alive. We use random walks to disseminate data from a sensor to a random subset of sensors in the network. Our algorithms take advantage of the low decoding complexity of fountain codes, as well as the scalability of the dissemination process via random walks. We have proposed two algorithms based on random walks. Our theoretical analysis and simulation-based studies have shown that, the first algorithm maintains the same level of fault tolerance as the original centralized fountain code, while introducing lower overhead than naive random-walk based implementation in the dissemination process. Our second algorithm has lower level of fault tolerance than the original centralized fountain code, but consumes much lower dissemination cost.

A Distributed Framework for Correlated Data Gathering in Sensor Networks

We consider the problem of correlated data gathering in sensor networks with multiple sink nodes. The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes such that the data gathered by the sink nodes can reproduce the field of observation. Second, we would like to find a transmission structure on the network graph such that the total transmission energy consumed by the network is minimized. The existing solutions to this problem are impractical for deployment because they have not considered all of the following factors: (1) distributed implementation; (2) capacity and interference associated with the shared medium; and (3) realistic data correlation model. In this paper, we propose a new distributed framework to achieve minimum energy data gathering while considering these three factors. Based on a localized version of Slepian-Wolf coding, the problem is modeled as an optimization formulation with a distributed solution. The formulation is first relaxed with Lagrangian dualization and then solved with the subgradient algorithm. The algorithm is amenable to fully distributed implementations, which corresponds to the decentralized nature of sensor networks. To evaluate its effectiveness, we have conducted extensive simulations under a variety of network environments. The results indicate that the algorithm supports asynchronous network settings, sink mobility, and duty schedules.

CodeOR: Opportunistic routing in wireless mesh networks with segmented network coding

Opportunistic routing significantly increases unicast throughput in wireless mesh networks by effectively utilizing the wireless broadcast medium. With network coding, opportunistic routing can be implemented in a simple and practical way without resorting to a complicated scheduling protocol. Due to constraints of computational complexity, a protocol utilizing network coding needs to perform segmented network coding, which partitions the data into multiple segments and encode only packets in the same segment. However, existing designs transmit only one segment at any given time while waiting for its acknowledgment, which degrades performance as the size of the network scales up. In this paper, we propose CodeOR, a new protocol that uses network coding in opportunistic routing to improve throughput. By transmitting a window of multiple segments concurrently, it improves the performance of existing work by a factor of two on average (and a factor of four in some cases). CodeOR is especially appropriate for real-time multimedia applications through the use of a small segment size to decrease decoding delay, and is able to further increase network throughput with a smaller packet size and a larger window size.

Stochastic analysis of network coding in epidemic routing

Epidemic routing has been proposed to reduce the data transmission delay in disruption tolerant wireless networks, in which data can be replicated along multiple opportunistic paths as different nodes move within each others communication range. With the advent of network coding, it is intuitive that data can not only be replicated, but also coded, when the transmission opportunity arises. However, will opportunistic communication with network coding perform any better than simple replications? In this paper, we present a stochastic analytical framework to study the performance of epidemic routing using network coding in opportunistic networks, as compared to the use of replication. We analytically show that network coding is superior when bandwidth and node buffers are limited, reflecting more realistic scenarios. Our analytical study is able to provide further insights towards future designs of efficient data communication protocols using network coding. As an example, we propose a priority based coding protocol, with which the destination can decode a high priority subset of the data much earlier than it can decode any data without the use of priorities. The correctness of our analytical results has also been confirmed by our extensive simulations.