Stavros Athanassopoulos

Experimental Comparison of Algorithms for Energy-Efficient Multicasting in Ad Hoc Networks

Energy is a scarce resource in ad hoc wireless networks and it is of paramount importance to use it efficiently when establishing communication patterns. In this work we study algorithms for computing energy-efficient multicast trees in ad hoc wireless networks. Such algorithms either start with an empty solution which is gradually augmented to a multicast tree (augmentation algorithms) or take as input an initial multicast tree and ’walk’ on different multicast trees for a finite number of steps until some acceptable decrease in energy consumption is achieved (local search algorithms).

Analysis of Approximation Algorithms for k -Set Cover Using Factor-Revealing Linear Programs

We present new combinatorial approximation algorithms for the k-set cover problem. Previous approaches are based on extending the greedy algorithm by efficiently handling small sets. The new algorithms further extend these approaches by utilizing the natural idea of computing large packings of elements into sets of large size. Our results improve the previously best approximation bounds for the k-set cover problem for all values of k≥6. The analysis technique used could be of independent interest; the upper bound on the approximation factor is obtained by bounding the objective value of a factor-revealing linear program.

An Improved Approximation Bound for Spanning Star Forest and Color Saving

We present a simple algorithm for the maximum spanning star forest problem. We take advantage of the fact that the problem is a special case of complementary set cover and we adapt an algorithm of Duh and Furer in order to solve it. We prove that this algorithm computes 193/240 ≈ 0.804-approximate spanning star forests; this result improves a previous lower bound of 0.71 by Chen et al. Although the algorithm is purely combinatorial, our analysis defines a linear program that uses a parameter f and which is feasible for values of the parameter f not smaller than the approximation ratio of the algorithm. The analysis is tight and, interestingly, it also applies to complementary versions of set cover such as color saving; it yields the same approximation guarantee of 193/240 that marginally improves the previously known upper bound of Duh and Furer. We also show that, in general, a natural class of local search algorithms do not provide better than 1/2-approximate spanning star forests.

Cellular automata for topology control in Wireless Sensor Networks

We use cellular automata for simulating topology control algorithms in Wireless Sensor Networks (WSNs). A cellular automaton is a decentralized computing model providing an excellent platform for performing complex computations using only local information. WSNs are composed of a large number of distributed sensor nodes operating on batteries; the objective of the topology control problem in WSNs is to select an appropriate subset of nodes able to monitor a region at a minimum energy consumption cost thus extending the network lifetime. We have used cellular automata to model a randomized WSN topology control algorithm and have experimentally evaluated its performance.

Energy-Efficient Communication in Multi-interface Wireless Networks

We study communication problems in wireless networks supporting multiple interfaces. In such networks, two nodes can communicate if they are close and share a common interface. The activation of each interface has a cost reflecting the energy consumed when a node uses this interface. We distinguish between the symmetric and non-symmetric case, depending on whether all nodes have the same activation cost for each interface or not. For the symmetric case, we present a (3/2 + ?)---approximation algorithm for the problem of achieving connectivity with minimum activation cost, improving a previous bound of 2. For the non-symmetric case, we show that the connectivity problem is not approximable within a sublogarithmic factor in the number of nodes and present a logarithmic approximation algorithm for a more general problem that models group communication.

Analysis of approximation algorithms for k -set cover using factor-revealing linear programs

We present new combinatorial approximation algorithms for k-set cover. Previous approaches are based on extending the greedy algorithm by efficiently handling small sets. The new algorithms further extend them by utilizing the natural idea of computing large packings of elements into sets of large size. Our results improve the previously best approximation bounds for the k-set cover problem for all values of k ≥ 6. The analysis technique could be of independent interest; the upper bound on the approximation factor is obtained by bounding the objective value of a factor-revealing linear program.

Cellular Automata for Topology Control in Wireless Sensor Networks Using Matlab

We use cellular automata for simulating topology control algorithms in Wireless Sensor Networks (WSNs). A cellular automaton is a decentralized computing model providing an excellent platform for performing complex computations using only local information. WSNs are composed of a large number of distributed sensor nodes operating on batteries; the objective of the topology control problem in WSNs is to select an appropriate subset of nodes able to monitor a region at a minimum energy consumption cost thus extending the network lifetime. We have used cellular automata to model a randomized WSN topology control algorithm and have experimentally evaluated its performance.

An experimental study of greedy routing algorithms

The “small world” phenomenon, i.e., the fact that the global social network is strongly connected in the sense that every two persons are inter-related through a small chain of friends, has attracted research attention and has been strongly related to the results of the social psychologists Stanley Milgram experiments; properties of social networks and relevant problems also emerge in peer-to-peer systems and their study can shed light on important modern network design properties. In this paper, we have experimentally studied greedy routing algorithms, i.e., algorithms that route information using “long-range” connections that function as shortcuts connecting “distant” network nodes. In particular, we have implemented greedy routing algorithms, and techniques from the recent literature in networks of line and grid topology using parallelization for increasing efficiency. To the best of our knowledge, no similar attempt has been made so far.

Experimental comparison of algorithms for interference control in ad-hoc wireless networks

Interference is an issue of outstanding importance for efficient communication in ad-hoc wireless networks. Interference arises due to overlapping transmission power levels of nodes and causes message collisions that require energy-consuming retransmissions. In this work we study algorithms for interference control in ad-hoc wireless networks in the Euclidean space that aim at constructing low-interference network topologies with particular properties preserving network connectivity. We survey relative research work on such algorithms and provide implementations for four such algorithms comparing them on random geometric instances of the problem in the Euclidean space in average-case networks. Our experiments show that our implementations obtain in practice improved performance compared to corresponding theoretical bounds. Our findings confirm that sparse topologies do not automatically imply low interference and, furthermore, imply that a unified model for decreasing simultaneously both edge- and node-interference remains hard to define.