Current collision resolution mechanisms in commu-nications are based on different versions of the binary exponential backoff (BEB) retransmission algorithm. According to it, each station doubles its contention window upon a new collision, and resets it to a minimum value after a successful transmission. Globally, the algorithm offers high throughput at the expense of relatively large access delay. In this paper, a new method is proposed that allows a central element to discover colliding stations and then schedule retransmissions without the risk of new collisions. The analysis reveals that the proposed method substantially outperforms the BEB algorithm used in WiFi networks in terms of throughput-delay performance.

In this paper, the comprehensive delay and performance analyses of the M-ary molecular communications with memory are presented. By taking into account any level of channel memory, the type-based and concentration-based modulation schemes are introduced and analyzed. In the type-based modulation, information symbols are encoded through different molecule types. In the concentration-based modulation, various concentration levels of one molecule type are used to encode information symbols. For both modulation schemes, the delay distributions of the molecular symbols are derived, and then, the symbol error probabilities are developed. The given distributions and the error probability expressions are validated through extensive simulation experiments. After showing that the derived expressions are valid, the performance of the modulation schemes is evaluated. The performance evaluations reveal that by properly selecting the parameters such as slot time and number of emitted molecules, the performance can be improved in both type and concentration-based molecular communication as the channel memory is increased. Furthermore, it is shown that the type-based molecular communication outperforms the concentration-based molecular communication.

To perform spectrum handoff, cognitive radio (CR) nodes communicating with each other need to exchange licensed user detection information, i.e., perform spectrum coordination, over a common control channel. The spectrum coordination can be fulfilled either via existing cognitive radio interface with time division or via a separate dedicated radio, i.e., a common control interface (CCI), continuously. CR nodes with CCI can instantly exchange licensed user detection information and cease frame transmission, while spectrum coordination can only be performed after the frame transmission period without CCI. Nevertheless, the impact of CCI incorporation into CR nodes in terms of common performance metrics must be thoroughly assessed to evaluate the worthiness of additional radio cost. In this paper, an analytical framework is presented to assess the impact of CCI incorporation into CR nodes for spectrum handoff. The developed framework enables analyzing potential benefits and disadvantages of employing CCI for spectrum handoff, in terms of achievable delay, energy consumption, spectrum utilization and event estimation performance. Extensive performance evaluations are presented to illustrate the impact of CCI utilization on efficiency of spectrum handoff. The network and communication regimes that would yield having CCI favorable are characterized in terms of spectrum conditions and CR parameters.

Virtual Multiple-Input Single-Output (MISO) is recently proposed to extend the benefits of transmitter space diversity to networks in which the deployment of antenna arrays on individual nodes is infeasible from a practical point of view. Ad-hoc and sensor networks are examples of these type of networks. In these scenarios, nodes equipped with single antenna can cooperatively transmit to emulate an antenna array. However, cooperative transmissions require knowledge of the channel state either at the transmitter side or the receiver side in order to achieve full performance gains. Several solutions are proposed in the literature under these assumptions, but at the expense of increased overhead and energy consumption. In this paper, the array gain at the receiver from the non-coherent combining of the signals from multiple transmitters is analyzed in statistical sense, under the assumption that the channel knowledge is unavailable. The transmitters are assumed to be randomly spread over a circular region. More specifically, exact or very accurate closed-form expressions for the expectation and variance of the array gain are obtained, and then a complete statistical distribution is postulated and validated by means of heuristic procedures, goodness-of-fit tests and specialized software. The results obtained in this paper can be especially useful for the implementation of two-tiered wide area sensor networks.

In a time-driven sensor network, monitored data are periodically reported to the base station via a data-gathering tree. Unfortunately, the problem of finding the spanning tree with maximum lifetime is known to be NP-complete. In this work-in-progress paper, we propose a genetic algorithm to solve this problem. We test it for small-sized networks, for which the optimal solution can be evaluated, and we obtain encouraging preliminary results in terms of correctness and computational complexity.

In this work we propose multi-objective simulated annealing as a heuristic technique for optimal routing in time-driven sensor networks. Unlike previous algorithms and methods, this technique is intended to tackle multiple performance-related and other design objectives in a computationally feasible way. Since these objectives are usually in conflict, the general solution is formulated as the so-called Pareto set, which is the set of non-dominated design vectors representing different tradeoffs.

Time-driven sensor networks are devoted to the continuous reporting of ambient data to the base station. In many cases, these data are provided by nodes that have been deployed in a structured manner, either by selecting strategic locations or by adopting some regular sampling pattern. In either case, the resulting inter-node distances may not be small, and thus additional supporting nodes may be necessary. This suggests that the problem could be better addressed from a network planning perspective. In this sense, a particular approach is proposed and, as part of it, the paper focuses on optimizing the lifetime that can be predicted from the network topology, which is assumed to be a static data gathering tree. It is shown that this problem requires the exploration of all possible spanning trees, since the energy consumed by a node depends on its workload, which in turn depends on how this node is connected to its neighborhood. Because this is an NP-hard problem, the use of a heuristic approach is required. Then, an algorithm based on simulated annealing is proposed, which converges asymptotically to the global optimum. This algorithm is tested on different scenarios and its computational complexity is proved to be linearly dependent on the number of nodes.

In this paper, the expected lifetime of a wireless sensor network devoted to vineyard monitoring is considered. This network uses a technique called random or stochastic sampling for the continuous tracking of the air temperature across the vineyard, and a pure Aloha protocol without retransmissions for the delivery of data to the base station. The design is based on the fact that the reconstruction process at the application layer can tolerate certain jitter in the sampling process. This is completely acceptable because of the strong temporal and spatial correlations exhibited by the environmental conditions across the sensor field. In addition to simplicity, the proposed implementation provides excellent results in terms of network lifetime. The design can also be extended to broader contexts, such as precision agriculture and habitat monitoring in general

In this paper, an exact solution for the response time distribution of a single server, infinite capacity, discrete-time queue is presented. This queue is fed by a flexible discrete-time arrival process, which follows an on/off evolution. A workload variable is associated with each arrival instant, which may correspond to the service demand generated by a single arrival, or represent the number of simultaneous arrivals (bulk arrivals). Accordingly, the analysis focuses on two types of queues: (On/Off)/G/1 and (Batch-On/Off)/D/1. For both cases, a decomposition approach is carried out, which divides the problem into two contributions: the response time experienced by single bursts in isolation, and the increase on the response time caused by the unfinished work that propagates from burst to burst. Particularly, the solution for the unfinished work is derived from a Wiener-Hopf factorization of random walks, which was already used in the analysis of discrete GI/G/1 queues. Compared to other related works, the procedure proposed in this paper is exact, valid for any traffic intensity and has no constraints on the distributions of the input random variables characterizing the process: duration of on and off periods, and workload. From the general solution, an efficient and robust iterative algorithm for computing the expected response time of both queues is developed, which can provide results at any desired precision. This algorithm is numerically evaluated for different types of input distributions and proved against simulation.

B-ISDN is conceived to support all types of existing and new emerging applications. In the context of B-ISDN and the new age of information, the user terminal will generate data, voice, video and, in general, multimedia traffic. ATM is the selected mechanism for the efficient transfer of these information across the future worldwide network. The proper design of this network requires cost-effective solutions that may satisfy the quality of service constraints of all the connections. To achieve this goal, an accurate characterization of the traffic generated by the sources is needed. This characterization should capture the statistical properties of the ATM traffic that are relevant to network performance. A review of literature shows that, from a general point of view, this objective has been reached, but with two drawbacks: traffic models are application dependant and, moreover, for some applications, traffic models are not analytically tractable. The final objective of this paper is to construct a general analytical B-ISDN model. Particularly, the paper focuses on the on-off models with general distributions, for which a complete exact statistical characterization at cell level was already obtained in a previous paper. On the basis of this characterization, an algorithm devoted to capture the statistical behaviour of any source is formulated and developed. Particularly, the algorithm captures the average rate and burstiness of any source in an exact way, and the autocorrelation function in an optimal way. Finally, numerical results for different types of video sources are provided.