Xiaoyu Chu

Cooperative topology control with adaptation for improved lifetime in wireless ad hoc networks

Topology control algorithms allow each node in a wireless multi-hop network to adjust the power at which it makes its transmissions and choose the set of neighbors with which it communicates directly, while preserving global goals such as connectivity or coverage. This allows each node to conserve energy and contribute to increasing the lifetime of the network. Previous work on topology control has largely used an approach based on considering only the energy costs across links without considering the amount of energy available on a node. Further, previous work has largely used a static approach where the topology is determined at the beginning of the networks life and does not incorporate the varying rates of energy consumption at different nodes. In this paper, we address these weaknesses and introduce a new topology control algorithm that dynamically adapts to current energy levels at nodes. The algorithm, called Cooperative Topology Control with Adaptation (CTCA), employs a game-theoretic approach that maps the problem of maximizing the networks lifetime into an ordinal potential game. This allows a node running the CTCA algorithm to make a sacrifice by increasing its transmission power if it can help reduce energy consumption at another node with a smaller lifetime. We prove the existence of a Nash equilibrium for the game. Our simulation results indicate that the CTCA algorithm extends the life of a network by more than 50% compared to the best previouslyknown algorithm.

Cooperative Topology Control with Adaptation for improved lifetime in wireless sensor networks

Topology control algorithms allow each node in a wireless multi-hop network to adjust the power at which it makes its transmissions and choose the set of neighbors with which it communicates directly, while preserving global goals such as connectivity or coverage. This allows each node to conserve energy and contribute to increasing the lifetime of the network. In this paper, we consider (i) both the energy costs of communication as well as the amount of available energy at each node, (ii) the realistic situation of varying rates of energy consumption at different nodes, and (iii) the fact that co-operation between nodes, where some nodes make a sacrifice by increasing energy consumption to help other nodes reduce their consumption, can be used to extend network lifetime. This paper introduces a new distributed topology control algorithm, called the Cooperative Topology Control with Adaptation (CTCA), based on a game-theoretic approach that maps the problem of maximizing the networks lifetime into an ordinal potential game. We prove the existence of a Nash equilibrium for the game. Our simulation results indicate that the CTCA algorithm extends the life of a network by more than 50% compared to other algorithms. We also study the performance of the distributed CTCA algorithm in comparison to an optimal centralized algorithm as a function of the communication ranges of nodes and node density.

An Energy Balanced dynamic Topology Control algorithm for improved network lifetime

In wireless sensor networks, a few sensor nodes end up being vulnerable to potentially rapid depletion of the battery reserves due to either their central location or just the traffic patterns generated by the application. In this paper, we use a new approach that balances the energy consumption at each of the nodes, thus increasing the functional lifetime of the network. We propose a new distributed dynamic topology control algorithm called Energy Balanced Topology Control (EBTC) which considers the actual energy consumed for each transmission and reception to achieve the goal of an increased functional lifetime. We analyze the algorithms computational and communication complexity and show that it is equivalent or lower in complexity to other dynamic topology control algorithms. Using an empirical model of energy consumption, we show that the EBTC algorithm increases the lifetime of a wireless sensor network by over 40% compared to the best of previously known algorithms.

On estimating the Spectral Radius of large graphs through subgraph sampling

Extremely large graphs, such as those representing the Web or online social networks, require prohibitively large computational resources for an analysis of any of their complex properties. In this paper, we investigate an algorithmic approach to overcoming this difficulty by inferring key properties of the full graph using a strategic sample of small subgraphs of the graph. We focus, in particular, on the spectral radius (the largest eigenvalue of the adjacency matrix) of the graph because of its relationship to multiple highly relevant properties of graphs. We describe the Spectral Radius Estimator (SRE), a new greedy algorithm based on adding nodes with high estimated eigenvalue centrality into sample subgraphs. We present results on the performance of the SRE on real-world graphs and show that it estimates the spectral radius of real graphs with 98% to 99.99% accuracy using a subgraph of size less than about 4% of the full graph. This work demonstrates the feasibility and the potential of subgraph sampling as a computationally cheap means of inferring complex properties of extremely large graphs.

A New Power-Aware Distributed Topology Control Algorithm for Wireless Ad Hoc Networks

Each node in a wireless multi-hop network can adjust the power at which it makes its transmissions and thus change the topology of the network to save energy by choosing a smaller number of neighbors with which it communicates directly. The Directed Relative Neighborhood Graph (DRNG) algorithm is among the most popular, efficient and versatile topology control algorithms that reduces energy costs while preserving connectivity. In this paper, however, we identify two key limitations of DRNG and address them in a new power-aware distributed topology control algorithm called Inclusive DRNG. We show that the Inclusive DRNG algorithm can cut down the energy cost of executing the topology control algorithm itself to as low as one-third that of executing DRNG. We further show that Inclusive DRNG also generates a topology that achieves a significant improvement of over 25% in the average energy cost of communication across a path between any two nodes in realistic irregular radio environments.

On improving the representation of a region achieved by a sensor network

This paper considers the class of applications of sensor networks in which each sensor node makes measurements, such as temperature or humidity, at the precise location of the node. Such spot-sensing applications approximate the physical condition of the entire region of interest by the measurements made at only the points where the sensor nodes are located. Given a certain density of nodes in a region, a more spatially uniform distribution of the nodes leads to a better approximation of the physical condition of the region in the sensed data. This paper considers the error in this approximation and seeks to improve the quality of representation of the physical condition of the points in the region in the data collected by the sensor network. We develop two essential metrics which together allow a rigorous quantitative assessment of the quality of representation achieved: the average representation error and the unevenness of representation error, the latter based on a well-accepted measure of inequality used in economics. We present the rationale behind the use of these metrics and derive relevant theoretical bounds on them in the common scenario of a planar region of arbitrary shape covered by a sensor network deployment. A simple new heuristic algorithm is presented for each node to determine if and when it should sense or sleep to conserve energy while also preserving the quality of representation. Simulation results show that it achieves a significant improvement in the quality of representation compared to other related distributed algorithms. Interestingly, our results also show that improved and consistent spatial uniformity has the welcome side-effect of a significant increase in the network lifetime.

The energy cost of mandatory bidirectionality in wireless multimedia communication

Features of network protocols, originally designed for good reasons when energy considerations were not paramount and multimedia communications were not common, are sometimes discovered to have high energy costs in new application domains involving multimedia. In this paper, we examine the energy cost of an old, simple and pervasive feature in wireless medium access control protocols: the mandatory acknowledgment at the link layer in response to a data frame, imposing the requirement that if node A can reach node B with its transmissions, then B should be able to reach A as well. We show that this mandated bidirectionality has a significant energy cost in ad hoc networks, multiplying the energy cost of a transmission at a node by as much as three. We also show that this negative impact increases further with increasing non-uniformity of the radio environment. Many multimedia applications are characterized by two features: a larger volume of traffic in one direction than in the reverse direction and by less of a need for immediate acknowledgement in the reverse direction. Mandated bidirectionality, therefore, carries an especially higher and unnecessary energy cost for multimedia communications. These findings suggest a new set of research problems on how best to design new features in protocols for medium access control for multimedia communications.