Junhua Zhu

Tradeoff Between Lifetime and Rate Allocation in Wireless Sensor Networks: A Cross Layer Approach

This paper studies the tradeoff between energy consumption and application performance in wireless sensor networks by investigating the interaction between network lifetime maximization and rate allocation problems. To guarantee the individual performance of sensor nodes, we adopt the network utility maximization (NUM) framework to ensure certain fairness on source rates of sensor nodes. We formulate the network lifetime maximization problem and fair rate allocation problem as constrained maximization problems, and combine them by introducing a system parameter, which characterizes the tradeoff between the two problems. Using Lagrange dual decomposition, the original problem is vertically decomposed into three subproblems: a rate control problem at the transport layer, a contention resolution problem at the MAC Layer, and a cross-layer energy conservation problem. The first and second subproblems jointly solve the congestion problem in sensor networks via congestion prices, and fully distributed algorithms are derived. Furthermore, they are coupled with the cross layer energy conservation problem to solve the network lifetime maximization problem via energy prices. For the third subproblem, we first propose a partially distributed algorithm where network lifetime is a global information, and then by exploring the similarity between max-min rate allocation and network lifetime maximization in sensor networks, we approximate the latter by the NUM framework, and hence formulate the tradeoff problem in the unified NUM framework. As a result, a fully distributed algorithm is derived for the energy conservation problem.

Tradeoff between network lifetime and fair rate allocation in wireless sensor networks with multi-path routing

The network lifetime and application performance are two fundamental but conflicting desig objectives in wireless sensor networks. Hence there is an intrinsic tradeoff between network lifetime maximization and application performance maximization. Often application performance correlates to the application data rate obtained in sensor networks. We can thus study this tradeoff by investigating the interactions between the network lifetime maximization problem and the rate allocation problem. Severe bias on the allocated rates of some sensor nodes may exist if only the total throughput of the sensor network is maximized, hence we enforce fairness on source rates of sensor nodes by invoking the network utility maximization (NUM) framework. First we consider the network lifetime as global information shared by sensor nodes. We formulate the network lifetime maximization and fair rate allocation both as constrained maximization problems. By introducing a system parameter, we combine these two objectives into a single weighted objective, and characterize the tradeoff between them. Then we give the optimality condition, and derive a partially distributed algorithm. Also, we identify the similarity between network lifetime maximization and max-min rate allocation in networks. Since the latter one can be approximated using NUM framework, we adopt the same idea for the former one, and approximate the optimal solution in the unified NUM framework. Based on this, an efficient fully distributed algorithm is derived.

Rate-lifetime tradeoff for reliable communication in wireless sensor networks

The network lifetime and application performance are two fundamental, yet conflicting, design objectives in wireless sensor networks. There is an intrinsic tradeoff between network lifetime maximization and application performance maximization, the latter being often correlated to the rate at which the application can send its data reliably in sensor networks. In this paper we study this tradeoff by investigating the interactions between the network lifetime maximization problem and the rate allocation problem with a reliable data delivery requirement. Severe bias on the allocated rates of some sensor nodes may exist if only the total throughput of the sensor network is maximized, hence we enforce fairness on source rates of sensor nodes by invoking the network utility maximization (NUM) framework. To guarantee reliable communication, we adopt the hop-by-hop retransmission scheme. We formulate the network lifetime maximization and fair rate allocation both as constrained maximization problems. We characterize the tradeoff between them, give the optimality condition, and derive a partially distributed algorithm to solve the problem. Furthermore, we propose an approximation of the tradeoff problem using NUM framework, and derive a fully distributed algorithm to solve the problem.

Adaptive medium access control for minimum energy reliable data delivery in wireless sensor networks

In this paper, we propose and study two adaptive media access control protocols to support probabilistic data delivery reliability in sensor networks using MAC layer retransmissions. Since retransmissions consume energy, our adaptive p-persistent CSMA protocols tune their persistence probabilities in an effort to minimize the expected number of retransmissions that meet a given probabilistic reliability requirement, and thereby minimize energy consumption in the network. We formulate this problem of reliability with minimal energy consumption at the MAC layer as a constrained optimization problem and then derive the algorithms to adapt the persistence probabilities using the Lagrangian dual decomposition method.

On Estimating the Bandwidth Share of TCP Connections in Presence of Reverse Traffic

To improve the performance of TCP under different network scenarios, the idea of adjusting congestion window according to the bandwidth share estimation has been widely used. Various estimators are proposed in the literature. Some estimate the acquired bandwidth share, and some estimate the volume of traffic or packets queued in the buffers along the end-to-end path. We evaluate these estimation techniques with a common and effective performance metric, the number of DATA packets queued in the buffers and notice that because most estimators do not distinguish explicitly between the queuing delay on the forward path and that on the reverse path, in presence of large volumes of traffic on the reverse path these estimators become fragile. To address this problem, we propose a one-way queuing delay estimation scheme which only requires simple modifications to current TCP implementation (through a TCP option). With this estimation scheme, a one-way packet in queue estimator (OPQE) is proposed to provide a more robust and accurate estimation of the number of DATA packets queued along the forward path of a TCP connection. Simulation results show that OPQE has a good performance under different scenarios, even in the presence of reverse traffic.

Minimum energy probabilistic reliable data delivery in wireless sensor networks

Many sensor network applications only require probabilistic data delivery, as they can tolerate some missing data samples. For example, in environmental monitoring, missing temperature, pressure and humidity level samples can often be inferred by spatial and/or temporal interpolations. In this paper we propose and study an adaptive p-persistent CSMA-based media access control protocol that supports end-to-end probabilistic reliability for sensor networks on a hop-by-hop basis. In an effort to reduce the probability of packet collisions, first we tune the carrier sensing range of the nodes; then given an end-to-end reliability requirement, we determine the optimal allocation of per-hop reliability requirements on each route to minimize the expected total number of transmissions needed; finally, our adaptive p-persistent CSMA protocol tunes its link persistence probability to further reduce the expected total number of transmissions, and thereby minimizes the energy consumption in the network. We formulate this latter problem as a constrained optimization problem, and then derive an algorithm to adapt the link persistence probabilities using the Lagrangian dual decomposition method.

F 2 -TCP: A fairer and TCP-friendlier congestion control protocol for high-speed networks

Several studies have shown that in high-speed networks it is likely that a large number of packets are dropped in a single loss event on a bottleneck link and a large portion of the ongoing flows are about to experience packet losses. Such synchronized losses among flows have negative effects on the performance of most loss-based congestion control protocols proposed for high-speed networks, especially with respect to fairness considerations. We propose in this paper F2-TCP, a new loss-based congestion control protocol for high-speed networks, to achieve better fairness and TCP-friendliness. Simulation studies show that F2-TCP indeed fulfills these design goals. The superior performance and the low deployment cost, especially on legacy machines, make F2-TCP a good alternative for todaypsilas high-speed networks.

Maximum Data Collection Least-Cost Routing in Energy Constrained Wireless Sensor Networks

Sensor networks are deployed to gather some useful data from a field and forward it toward a set of base stations or sinks for data analysis and decision making. Each sensor node is endowed with a finite amount of energy, and each byte transmission or reception costs a certain fixed fraction of energy as well as a variable fraction that depends on the distance between sender and receiver. Maximizing the volume of data collected at the sinks until some particular set of nodes exhaust their battery and partition the network is a very desirable trait in sensor networks, as it equates with a high level of energy efficiency. In this paper we formulate the problem of maximum data collection routing for sensor networks as a utility maximization problem subject to energy constraints, and invoke lagrange relaxation, duality and sub-gradient technique to solve the problem. We then focus on the problem of path oscillation, which is well known to happen in routing algorithms where link costs are function of the traffic load and propose heuristic solutions to address this oscillation problem