Attila Vidács

Deploying Multiple Sinks in Multi-hop Wireless Sensor Networks

Due to the scarce energy supplies of a wireless sensor network (WSN) it is necessary to design the architecture and operation of the network so as to optimize the energy consumption. Since in a multi-hop WSN a sensor spends most of its energy for relaying data packets it is important to shorten the distance a packet has to travel until reaching the sink. These distances can be reduced seriously by deploying multiple sinks instead of one. In that case every sensor communicates with the closest sink. In order to achieve the shortest distances the sinks have to be deployed in a coordinated way. In this paper we give a mathematical model that determines the locations of the sinks minimizing the sensors average distance from the nearest sink. First we present an iterative algorithm called global that is able to find the sink locations given by the mathematical model. However, it uses global information about the network that is impractical in wide area sensor networks, thus we propose a novel iterative algorithm called lhop that carries out the sink deployment based only on the location information of the neighboring nodes while the location of the distant nodes is being approximated. We compared the two algorithms and show that lhop approaches the performance of global very closely. Another important issue is that the neighboring nodes of the sinks have a high traffic load, thus the lifetime of the network can be elongated by relocating the sinks from time to time. Based on the lhop algorithm we propose the lhop relocation algorithm for the coordinated relocation of multiple sinks. The simulation results show that the algorithm extend the network lifetime severely.

Adaptive sink mobility in event-driven multi-hop wireless sensor networks

Optimizing energy consumption in wireless sensor networks is of paramount importance. There is a recent trend to deal with this problem by introducing mobile elements (sensors or sink nodes) in the network. The majority of these approaches assume time-driven scenarios and/or single-hop communication between participating nodes. However, there are several real-life applications for which an event-based and multi-hop operation is more appropriate. In this paper we propose to adaptively move the sink node inside the covered region, according to the evolution of current events, so as to minimize the energy consumption incurred by the multi-hop transmission of the event-related data. Both analytical and simulation results are given for two optimization strategies: minimizing the overall energy consumption, and minimizing the maximum load on a specific sensor respectively. We show that by adaptively moving the sink, significant power saving can be achieved, prolonging the lifetime of the network.

Distributed Data Agregation with Geographical Routing in Wireless Sensor Networks

In wireless sensor networking applications, gathering sensed information and relaying it to the sink node using multi-hop communication in an energy efficient manner is of paramount importance. In this paper we present the idea of using aggregator nodes in order to decrease the amount of packets sent, hence reducing the energy required for communication. We introduce DDAP, a self-organizing distributed data aggregation protocol that uses randomly chosen aggregator nodes (ANs). We propose an extension of GOAFR, a robust geographical routing algorithm, collaborating with DDAP called geographical routing with aggregation nodes (GRAN). Simulation results evaluating the performance of DDAP and GRAN are presented. We show that by using DDAP and GRAN significant reduction in data traffic can be achieved, resulting in power saving and thus network lifetime prolongation.

Energy Efficiency in Wireless Sensor Networks Using Mobile Base Station

A sensor network consists of a large number of small, low-cost devices with sensing, processing and transmitting capabilities. The sensor nodes have limited battery power; therefore energy efficiency is a critical design issue. In this paper we propose to move the sink node, called Base Station (BS) so as to decrease the energy consumption of the whole network. We present two possible strategies to move the BS: the first one minimizes the average consumed energy, while the other one minimizes the maximum transmission energy for every active sensor. To evaluate the performance of the two strategies, we compare these with the case, when the BS is deployed in a fixed position. Simulation results show that the proposed processes can reduce energy consumption, thereby significantly extending the lifetime of the entire sensor network.

Positioning mobile base station to prolong wireless sensor network lifetime

Energy efficiency is a critical issue in designing sensor networks, as the nodes have limited battery power. In this paper we propose to move the BS so as to prolong the network lifetime. We present three strategies for moving the BS: (1) minimizing the average transmission energy; (2) minimizing the maximum transmission energy; and (3) minimizing the maximum relative consumed energy for every active sensor. We examined the case, when the BS is on the optimal location in each round using the three strategies.

On incentives in global wireless communities

The wireless community networking paradigm shows great promise in achieving a global status. However, both user participation and support from traditional Internet Service Providers (ISPs) play key roles in creating worldwide coverage; for this end a viable incentive system is essential. In this paper we study the economic interactions between users, ISPs and community providers. Our main contribution is threefold. First, we propose a model of the global wireless community concept as a Stackelberg game of two levels and construct the respective payoff functions of each player. Second, we show how both users and ISPs may fail to join the community in equilibrium. Third, we explore the parameter space of the mechanism designer and show how the technology diffusion process and expected payoffs can be controlled by adjusting roaming prices and revenue shares.

Interference-Tolerant Spatio-Temporal Dynamic Spectrum Allocation

The radio spectrum is a scarce and thus expensive resource. The exclusive licences of todays practice easily solve the problem of interference, but is clearly inadequate for providing optimal spectrum efficiency for dynamically varying demands. We propose a new model for dynamic spectrum allocation (DSA) to increase spectral efficiency, that handles interference issues in a flexible way. The level of interference between different radio technologies and between geographic regions is captured by the introduced radio technology coupling and geometric coupling parameters. The tolerance for interference from the radio network providers point of view is also taken into account. The rules for a feasible spectrum allocation are given, and the optimal allocation that maximizes the achievable gain is calculated using heuristics. Simulation results show the effectiveness of the proposed DSA model for different scenarios.

Techniques to improve scheduling performance in IEEE 802.15.3 based ad hoc networks

In this paper we propose new techniques to improve scheduling performance in time-slotted superframe based ad hoc networks. Such channel access technology is used in the IEEE 802.15.3 and 802.15.4 standards. Building on the performance analysis of previous proposals, we enhance the scheduling algorithms with flow state signaling and burst eligibility decision, so as to exploit the features of the 802.15.3 architecture. We show by simulation that the scheduling algorithms extended with these special mechanisms achieve higher performance, with better channel utilization and lower power consumption

Spatio-Temporal Dynamic Spectrum Allocation with Interference Handling

As for today, radio spectrum resource is rigidly partitioned for dedicated purposes. The exclusive license of fixed size spectrum blocks separated by guard bands easily solves the interference problems; however, the rigid allocation of spectrum is clearly inadequate for providing optimal spectrum efficiency for spatially and temporarily varying loads. Dynamic spectrum allocation (DSA) is a new and promising alternative where the assigned spectrum blocks may vary in time and space, too. In this paper we describe a spatio-temporal DSA model that splits the complex problem into temporal and spatial dynamic spectrum allocation. In our architecture the spectrum is allocated by regional spectrum brokers (RSB) that also coordinate spectrum access between regions. The problem of interference between different regions and providers is handled by a flexible description using the proposed geographical and radio technology coupling parameters. We also show how the optimal allocation can be found by giving the ILP solution to the problem. To evaluate the efficiency of the proposed DSA method, different gains are defined from the regulators point of view. The performance evaluation is carried out using computer simulations, and the results are compared with the cases where either there is no interference allowed at all, or interference does not occur between regions.

Spatio-temporal spectrum management model for dynamic spectrum access networks

Currently radio network resource is rigidly partitioned for dedicated purposes. Most of the spectrum is already allocated, but a large part of it is underutilized and the utilization varies greatly in time and space. The exclusive license of fixed size spectrum blocks separated by fixed guard bands easily solves the interference problems; however, the fixed allocation of spectrum is clearly inadequate for providing optimal spectrum efficiency for spatially and temporarily varying loads.n Dynamic spectrum allocation is a new and promising alternative to fixed allocation schemes. In Dynamic Spectrum Access (DSA) networks the assigned spectrum block may vary in time and space, too.n In this paper we describe a new spatio-temporal spectrum management model for DSA networks. We also describe an architecture that splits the complex problem into Temporal and Spatial Dynamic Spectrum Allocation (TDSA and SDSA). In our model Regional Spectrum Brokers (RSB) coordinate the temporal dynamic spectrum allocation for a given region within which we assume that the spatial distribution of the spectrum demand is homogeneous. There is a centralized entity also, called Spectrum Broker Coordinator (SBC), which stores the spectrum demands of the regions, and the spectrum management at the borders of the regions is realized based on this information.