Evi Papaioannou

Efficient On-Line Frequency Allocation and Call Control in Cellular Networks

Abstract In this paper we consider communication issues arising in cellular (mobile) networks that utilize frequency division multiplexing (FDM) technology. In such networks, many users within the same geographical region can communicate simultaneously with other users of the network using distinct frequencies. The spectrum of available frequencies is limited; thus, efficient solutions to the frequency-allocation and the call-control problems are essential. In the frequency-allocation problem, given users that wish to communicate, the objective is to minimize the required spectrum of frequencies so that communication can be established without signal interference. The objective of the call-control problem is, given a spectrum of available frequencies and users that wish to communicate, to maximize the number of users served. We consider cellular, planar, and arbitrary network topologies. In particular, we study the on-line version of both problems using competitive analysis. For frequency allocation in cellular networks, we improve the best known competitive ratio upper bound of 3 achieved by the folklore Fixed Allocation algorithm, by presenting an almost tight competitive analysis for the greedy algorithm; we prove that its competitive ratio is between 2.429 and 2.5 . For the call-control problem, we present the first randomized algorithm that beats the deterministic lower bound of 3 achieving a competitive ratio between 2.469 and 2.651 for cellular networks. Our analysis has interesting extensions to arbitrary networks. Also, using Yaos Minimax Principle, we prove two lower bounds of 1.857 and 2.086 on the competitive ratio of randomized call-control algorithms for cellular and arbitrary planar networks, respectively.

The impact of altruism on the efficiency of atomic congestion games

We study the effect of combining selfishness and altruism in atomic congestion games. We allow players to be partially altruistic and partially selfish and determine the impact of this behavior on the overall system performance. Surprisingly, our results indicate that, in general, by allowing players to be (even partially) altruistic, the overall system performance deteriorates. Instead, for the class of symmetric load balancing games, a balance between selfish and altruistic behavior improves system performance to optimality.

A tight bound for online colouring of disk graphs

We present an improved upper bound on the competitiveness of the online colouring algorithm First-Fit in disk graphs, which are graphs representing overlaps of disks on the plane. We also show that this bound is best possible for deterministic online colouring algorithms that do not use the disk representation of the input graph. We also present a related new lower bound for unit disk graphs.

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.

Randomized on-line algorithms and lower bounds for computing large independent sets in disk graphs

We study the on-line version of the maximum independent set problem, for the case of disk graphs which are graphs resulting from intersections of disks on the plane. In particular, we investigate whether randomization can be used to break known lower bounds for deterministic on-line independent set algorithms and present new upper and lower bounds.

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.

A tight bound for online coloring of disk graphs

We present an improved upper bound on the competitiveness of the online coloring algorithm First-Fit in disk graphs which are graphs representing overlaps of disks on the plane. We also show that this bound is best possible for deterministic online coloring algorithms that do not use the disk representation of the input graph. We also present a related new lower bound for unit disk graphs.

Efficient on-line communication in cellular networks

In this paper we consider communication issues arising in mobile networks that utilize Frequency Division Multiplexing (FDM) technology. In such networks, many users within the same geographical region can communicate simultaneously with other users of the network using distinct frequencies. The spectrum of available frequencies is limited; thus, efficient solutions to the frequency allocation and the call control problem are essential. In the frequency allocation problem, given users that wish to communicate, the objective is to minimize the required spectrum of frequencies so that communication can be established without signal interference. The objective of the call control problem is, given a spectrum of available frequencies and users that wish to communicate, to maximize the number of users served. We consider cellular, planar, and arbitrary network topologies. In particular, we study the on-line version of both problems using competitive analysis. For frequency allocation in cellular networks, we improve the best known competitive ratio upper bound of 3 achieved by the folklore Fixed Allocation algorithm, by presenting an almost tight competitive analysis for the greedy algorithm; we prove that its competitive ratio is between 2.429 and 2.5. For the call control problem, we present the first randomized algorithm that beats the deterministic lower bound of 3 achieving a competitive ratio of 2.934 in cellular networks. Our analysis has interesting extensions to arbitrary networks. Also, using Yaos Minimax Principle, we prove two lower bounds of 1.857 and 2.086 on the competitive ratio of randomized call control algorithms for cellular and arbitrary planar networks, respectively.

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.