Zhenzhen Ye

Optimal Policies for Distributed Data Aggregation in Wireless Sensor Networks

We consider the scenario of distributed data aggregation in wireless sensor networks, where each sensor can obtain and estimate the information of the whole sensing field through local data exchange and aggregation. The intrinsic trade-off between energy and delay in aggregation operations imposes a crucial question on nodes to decide optimal instants for forwarding their samples. The samples could be composed of the information from their own sensor readings or an aggregation of information with other samples forwarded from neighboring nodes. By considering the randomness of the sample arrival instants and the uncertainty of the availability of the multiaccess communication channel due to the asynchronous nature of information exchange among neighboring nodes, we propose a decision process model to analyze this problem and determine the optimal decision policies at nodes with local information. We show that, once the statistics of the sample arrival and the availability of the channel satisfy certain conditions, there exist optimal control-limit type policies which are easy to implement in practice. In the case that the required conditions are not satisfied, we provide two learning algorithms to solve a finite-state approximation model of the decision problem. Simulations on a practical distributed data aggregation scenario demonstrate the effectiveness of the developed policies, which can also achieve a desired energy-delay tradeoff.

Optimal stochastic policies for distributed data aggregation in wireless sensor networks

The scenario of distributed data aggregation in wireless sensor networks is considered, where sensors can obtain and estimate the information of the whole sensing field through local data exchange and aggregation. An intrinsic tradeoff between energy and aggregation delay is identified, where nodes must decide optimal instants for forwarding samples. The samples could be from a nodes own sensor readings or an aggregation with samples forwarded from neighboring nodes. By considering the randomness of the sample arrival instants and the uncertainty of the availability of the multiaccess communication channel, a sequential decision process model is proposed to analyze this problem and determine optimal decision policies with local information. It is shown that, once the statistics of the sample arrival and the availability of the channel satisfy certain conditions, there exist optimal control-limit-type policies that are easy to implement in practice. In the case that the required conditions are not satisfied, the performance loss of using the proposed control-limit-type policies is characterized. In general cases, a finite-state approximation is proposed and two on-line algorithms are provided to solve it. Practical distributed data aggregation simulations demonstrate the effectiveness of the developed policies, which also achieve a desired energy-delay tradeoff.

Optimal Stochastic Location Updates in Mobile Ad Hoc Networks

We consider the location service in a mobile ad-hoc network (MANET), where each node needs to maintain its location information by 1) frequently updating its location information within its neighboring region, which is called neighborhood update (NU), and 2) occasionally updating its location information to certain distributed location server in the network, which is called location server update (LSU). The trade off between the operation costs in location updates and the performance losses of the target application due to location inaccuracies (i.e., application costs) imposes a crucial question for nodes to decide the optimal strategy to update their location information, where the optimality is in the sense of minimizing the overall costs. In this paper, we develop a stochastic sequential decision framework to analyze this problem. Under a Markovian mobility model, the location update decision problem is modeled as a Markov Decision Process (MDP). We first investigate the monotonicity properties of optimal NU and LSU operations with respect to location inaccuracies under a general cost setting. Then, given a separable cost structure, we show that the location update decisions of NU and LSU can be independently carried out without loss of optimality, i.e., a separation property. From the discovered separation property of the problem structure and the monotonicity properties of optimal actions, we find that 1) there always exists a simple optimal threshold-based update rule for LSU operations; 2) for NU operations, an optimal threshold-based update rule exists in a low-mobility scenario. In the case that no a priori knowledge of the MDP model is available, we also introduce a practical model-free learning approach to find a near-optimal solution for the problem.

A Low-Complexity Synchronization Design for MB-OFDM Ultra-Wideband Systems

In this paper, we investigate the low-complexity synchronization design for multi-band orthogonal-frequency-division-multiplexing (MB-OFDM) ultra-wideband (UWB) systems. We propose a unified synchronizer design based on auto-correlation-function. The key component in the proposed synchronizer is a parallel signal detector structure in which multiple auto-correlation units are instantiated and their outputs are shared by other functional units in the synchronizer, including time-frequency pattern detection, symbol timing, carrier frequency offset estimation and correction and frame synchronization. We show that, via analysis and simulations, such a design achieves not only a low computation cost which makes it attractive in implementation, but also equal or better performance compared to the cross-correlation based designs.

A Synchronization Design for UWB-Based Wireless Multimedia Systems

Multi-band orthogonal frequency-division multiplexing (MB-OFDM) ultra-wideband (UWB) technology offers large throughput, low latency and has been adopted in wireless audio/video (AV) network products. The complexity and power consumption, however, are still major hurdles for the technology to be widely adopted. In this paper, we propose a unified synchronizer design targeted for MB-OFDM transceiver that achieves high performance with low implementation complexity. The key component of the proposed synchronizer is a parallel auto-correlator structure in which multiple ACF units are instantiated and their outputs are shared by functional blocks in the synchronizer, including preamble signal detection, time-frequency code identification, symbol timing, carrier frequency offset estimation and frame synchronization. This common structure not only reduces the hardware cost but also minimizes the number of operations in the functional blocks in the synchronizer as the results of a large portion of computation can be shared among different functional blocks. To mitigate the effect of narrowband interference (NBI) on UWB systems, we also propose a low-complexity ACF-based frequency detector to facilitate the design of (adaptive) notch filter in analog/digital domain. The theoretical analysis and simulation show that the performance of the proposed design is close to optimal, while the complexity is significantly reduced compared to existing work.

A unified model for joint throughput-overhead analysis of mobile ad hoc networks

We develop an analytical framework to study the throughput and routing overhead for proactive and reactive routing strategies in random access mobile ad hoc networks. To characterize the coexistence of the routing control traffic and data traffic, we model the interaction as a multi-class queue model at each node, where the aggregate control traffic and data traffic are two different classes of customers of the queue. We investigate the scaling property of the throughput, maximum mobility degree supported by the network and mobility-induced throughput deficiencies, under both classes of routing strategies. The proposed analytical model can be extended to incorporate various optimization techniques in routing. We present one exemplary technique and discuss its impacts on the scaling properties of throughput and routing overhead. The connection between the derived throughput result and some well-known network throughput capacity results in the literature is also addressed.

A unified model for joint throughput-overhead analysis of random access mobile ad hoc networks

An analytical framework is developed to study the throughput and routing overhead for proactive and reactive routing strategies in random access mobile ad hoc networks. To characterize the coexistence of the routing control traffic and data traffic, the interaction is modeled as a multi-class queue at each node, where the aggregate control traffic and data traffic are two different classes of customers of the queue. With the proposed model, the scaling properties of the throughput, maximum mobility degree supported by the network and mobility-induced throughput deficiencies are investigated, under both classes of routing strategies. The proposed analytical model can be extended to evaluate various routing optimization techniques as well as to study routing/relaying strategies other than conventional proactive or reactive routing. The connection between the derived throughput result and some well-known network throughput capacity results in the literature is also established.

Layered Sequential Decision Policies for Cross-Layer Design of Wireless Ad-Hoc Networks

Efficient transmission control (e.g., power/rate control) in the physical layer, link scheduling in the link layer and routing in the network layer are critical design issues of wireless ad hoc networks. By considering both the quality-of-service and the utilization of resources under the temporally correlated uncertainties of the network conditions, a sequential decision framework is proposed for protocol design and layering. By observing that there are usually different performance concerns in the network layer versus lower layers, two correlated sequential decision models for the operations at different layers are proposed. With the decision model in the link and physical layers, scheduling and transmission control are jointly optimized. By adding a decision model in the network layer, the benefit of cross-layer information is quantified and the optimal routing/forwarding strategy is characterized. Practical algorithms based on the proposed decision models are also developed to achieve optimal/near-optimal performance.

Optimal Location Updates in Mobile Ad Hoc Networks: A Separable Cost Case

We consider the location service in a mobile ad-hoc network (MANET), where each node needs to maintain its location information in the network by (i) frequently updating its location information within its neighboring region, which is called neighborhood update (NU), and (ii) occasionally updating its location information to a certain (fixed) distributed location server in the network, which is called location server update (LU). A trade-off exists between the costs in location update operations, on one hand, and the additional incurred costs in (position-based) routing due to location errors, on the other hand. In this paper, we develop a stochastic sequential decision framework to analyze this trade-off and provide design guidelines on selecting good location update strategies in practice. Under a Markovian mobility model, the location update decision problem is modeled as a Markovian decision process (MDP). Based on the separable cost structure of the proposed MDP model, we first show that the location update decisions on NU and LU can be independently carried out without loss of optimality. Then we investigate the optimality of simple threshold-based updating rules in NU and LU operations. We finally introduce a model-free learning approach which is practically useful to find a near-optimal solution for the problem.