The wireless sensor networks have long been an attractive field to the researchers and scientists for its ease in deployment and maintenance. In this research, we focus on the maximization of network lifetime which has become a critical issue in sensor networks. Clustered organization of nodes with aggregation of data at the cluster head becomes one of the significant means to extend life expectancy of the network. This paper proposes Particle Swarm Optimization (PSO) approach for generating energy-aware clusters by optimal selection of cluster heads. The PSO eventually reduces the cost of locating optimal position for the head nodes in a cluster. In addition, we have implemented the PSO-based approach within the cluster rather than base station, which makes it a semi-distributed method. The selection criteria of the objective function are based on the residual energy, intra-cluster distance, node degree and head count of the probable cluster heads. Furthermore, influence of the expected number of packet retransmissions along the estimated path towards the cluster head is also reflected in our proposed energy consumption model. The performance evaluation of our proposed technique is carried out with respect to the well-known cluster-based sensor network protocols, LEACH-C and PSO-C respectively. Finally, the simulation clarifies the effectiveness of our proposed work over its comparatives in terms of network lifetime, average packet transmissions, cluster head selection rounds supported by PSO and average energy consumption.

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In wireless sensor network, data fusion is considered an essential process for preserving sensor energy. Periodic data sampling leads to enormous collection of raw facts, the transmission of which would rapidly deplete the sensor power. In this paper, we have performed data aggregation on the basis of entropy of the sensors. The entropy is computed from the proposed local and global probability models. The models provide assistance in extracting high precision data from the sensor nodes. We have also proposed an energy efficient method for clustering the nodes in the network. Initially, sensors sensing the same category of data are placed within a distinct cluster. The remaining unclustered sensors estimate their divergence with respect to the clustered neighbors and ultimately join the least-divergent cluster. The overall performance of our proposed methods is evaluated using NS-2 simulator in terms of convergence rate, aggregation cycles, average packet drops, transmission cost and network lifetime. Finally, the simulation results establish the validity and efficiency of our approach.

A broad variety of location dependent services will become feasible in the near future due to the use of the Global Position System (GPS), which provides location information (latitude, longitude and possibly height) and global timing to mobile users. Routing is a problem of sending a message from a source to a destination. Geocasting is the problem of sending a message to all nodes located within a region (e.g. circle or square). Recently, several localized GPS based routing and geocasting protocols for a mobile ad hoc network were reported in literature. In directional (DIR) routing and geocasting methods, node A (the source or intermediate node) transmits a message m to all neighbors located between the two tangents from A to the region that could contain the destination. It was shown that memoryless directional methods may create loops in routing process.In two other proposed methods (proven to be loop-free), geographic distance (GEDIR) or most forward progress within radius (MFR) routing, node A forwards the message to its neighbor who is closest to destination, or has greatest progress toward destination (respectively). In this paper, we propose a general algorithm (based on an unified framework for both routing and geocasting problems), in which message is forwarded to exactly those neighbors which may be best choices for a possible position of destination (using the appropriate criterion). We then propose and discuss new V-GEDIR and CH-MFR methods and define R-DIR, modified version of existing directional methods. In V-GEDIR method, these neighbors are determined by intersecting the Voronoi diagram of neighbors with the circle (or rectangle) of possible positions of destination, while the portion of the convex hull of neighboring nodes is analogously used in the CH-MFR method. Routing and geocasting algorithms differ only inside the circle/rectangle. We propose memoryless and past traffic memorization variants of each scheme. The proposed methods may be also used for the destination search phase allowing the application of different routing schemes after the exact position of destination is discovered. Memoryless V-GEDIR and CH-MFR algorithms are loop free, and have smaller flooding rate (with similar success rate) compared to directional method. Simulations, involving the proposed and some known algorithms, are in progress and confirm our expectations.

In this paper, we use the blending functions of Lupaş type (rational) (p, q)-Bernstein operators based on (p, q)-integers for construction of Lupaş (p, q)-Bézier curves (rational curves) and surfaces (rational surfaces) with shape parameters. We study the nature of degree elevation and degree reduction for Lupaş (p, q)-Bézier Bernstein functions. Parametric curves are represented using Lupaş (p, q)-Bernstein basis.We introduce affine de Casteljau algorithm for Lupaş type (p, q)-Bernstein Bézier curves. The new curves have some properties similar to q-Bézier curves. Moreover, we construct the corresponding tensor product surfaces over the rectangular domain (u, v) ∈ [0, 1] × [0, 1] depending on four parameters. We also study the de Casteljau algorithm and degree evaluation properties of the surfaces for these generalization over the rectangular domain. Furthermore, some fundamental properties for Lupaş type (p, q)-Bernstein Bézier curves and surfaces are discussed. We get q-Bézier surfaces for (u, v) ∈ [0, 1] × [0, 1] when we set the parameter p 1 = p 2 = 1. In comparison to q-Bézier curves and surfaces based on Lupaş q-Bernstein polynomials, our generalization gives us more flexibility in controlling the shapes of curves and surfaces.We also show that the (p, q)-analogue of Lupaş Bernstein operator sequence L n pn,qn (f, x) converges uniformly to f (x) ∈ C[0, 1] if and only if 0 < q n < p n ≤ 1 such that lim n→∞ q n = 1, lim n→∞ p n = 1 and lim n→∞ p n n = a, lim n→∞ q n n = b with 0 < a, b ≤ 1. On the other hand, for any p > 0 fixed and p = 1, the sequence L n p,q (f, x) converges uniformly to f (x) ∈ C[0, 1] if and only if f (x) = ax + b for some a, b ∈ R.

In this paper, we propose a general algorithm (based on an unified framework for both routing and geocasting problems), in which message is forwarded to exactly those neighbors which may be best choices for a possible position of destination (using the appropriate criterion). We then propose and discuss new VD‐GREEDY and CH‐MFR methods and define R‐DIR, modified version of existing directional methods. In VD‐GREEDY method, these neighbors are determined by intersecting the Voronoi diagram of neighbors with the circle (or rectangle) of possible positions of destination, while the portion of the convex hull of neighboring nodes is analogously used in the CH‐MFR method. Routing and geocasting algorithms differ only inside the circle/rectangle. The proposed methods may be also used for the destination search phase allowing the application of different routing schemes after the exact position of destination is discovered. VD‐GREEDY and CH‐MFR algorithms are loop free, and have smaller flooding rate (with similar success rate) compared to directional method. We proposed to use dominating set concept to reduce flooding ratio significantly, with a marginal impact on success rate and hop count. Simulations, involving the proposed and some known algorithms, are performed for two basic scenarios, one for geocasting and reactive routing, and the other for proactive routing, and both showed that our methods have higher success rate and lower flooding rate compared to existing methods. Copyright © 2006 John Wiley & Sons, Ltd.

Wireless multimedia sensor networks (WMSNs) are capable of collecting multimedia events, such as traffic accidents and wildlife tracking, as well as scalar data. As a result, WMSNs are receiving a great deal of attention both from industry and academic communities. However, multimedia applications tend to generate high volume network traffic, which results in very high energy consumption. As energy is a prime resource in WMSN, an efficient routing algorithm that effectively deals with the dynamic topology of WMSN but also prolongs the lifetime of WMSN is required. To this end, we propose a routing algorithm that combines dynamic cluster formation, cluster head selection, and multipath routing formation for data communication to reduce energy consumption as well as routing overheads. The proposed algorithm uses a genetic algorithm (GA)-based meta-heuristic optimization to dynamically select the best path based on the cost function with the minimum distance and the least energy dissipation. We carried out an extensive performance analysis of the proposed algorithm and compared it with three other routing protocols. The results of the performance analysis showed that the proposed algorithm outperformed the three other routing protocols.

Sensing coverage problem in wireless sensor networks is a measure of quality of service (QoS). Coverage refers to how well a sensing field is monitored or tracked by the sensors. Aim of the paper is to have a priori estimate for number of sensors to be deployed in a harsh environment to achieve desired coverage. We have proposed a new sensing channel model that considers combined impact of shadowing fading and multipath effects. A mathematical model for calculating coverage probability in the presence of multipath fading combined with shadowing is derived based on received signal strength (RSS). Further, the coverage probability derivations obtained using Rayleigh fading and lognormal shadowing fading are validated by node deployment using Poisson distribution. A comparative study between our proposed sensing channel model and different existing sensing models for the network coverage has also been presented. Our proposed sensing model is more suitable for realistic environment since it determines the optimum number of sensors required for desirable coverage in fading conditions.