Mohammad Abdul Azim

Performance Evaluation of Optimized Forwarding Strategy for Flat Sensor Networks

Network lifetime is the most important concern in designing a routing protocol for wireless sensor networks. To address the issue we have proposed optimized forwarding by fuzzy inference systems (OFFIS) for flat sensor networks [1]. The OFFIS protocol selects the best node from candidate nodes in the forwarding paths by favoring small hops, shortest path, maximum remaining battery power and link usage. The core strategy of OFFIS is to conserve as well as to distribute energy dissipation evenly in a decentralized manner. In this paper we compare OFFIS with the minimum transmit energy (MTE) technique and show that the lifetime can be improved notably.

Two-Layer Optimized Forwarding for Cluster-Based Sensor Networks

Wireless sensor networks (WSNs) usually contain a large number of nodes typically with highly correlated collected data. To support large-scale wireless sensor network management and local data aggregation, hierarchical routing techniques can be regarded as superior to flat routing approaches. Low power consumption as well as smart way of distributing the load is crucial to the routing protocol design in order to attain elongated WSN lifetime. We have already proposed a distributed routing algorithm; optimized forwarding by fuzzy inference systems (OFFIS) for the flat networks, where the decision is based on the distance power and link uses. In this paper, we propose a two-layer OFFIS (2L-OFFIS) for environmental data collection in cluster-based sensor networks. Simulation results show that the network lifetime can be significantly elongated by utilizing the new protocol in hierarchical sensor networks

Localization in wireless sensor networks by constrained simultaneous perturbation stochastic approximation technique

Localization of sensor networks poses an immense challenge and is considered as a hot research topic in recent days. To address the accuracy on localization this paper proposes constrained simultaneous perturbation stochastic approximation (SPSA) based localization techniques for wireless sensor networks. A simple centralized localization of the non-anchor nodes based on minimizing the summation of the estimated error of all neighbors is the basic building block of the proposed localization technique. This category of localization technique incurs errors often referred as flip ambiguity. The improvement of the simple SPSA based localization is made by modifying the algorithm to a constrained optimization technique using penalty function method where the correction on the flipped node is made by penalizing the identified flips by the penalty function. Simulation results demonstrate the superiority of the proposed SPSA algorithm compared to its closest counterpart, namely, the simulated annealing (SA) based localization algorithm.

Localization in Wireless Sensor Networks by Cross Entropy Method

Wireless sensor network (WSN) localization technique remains an open research issue due to its challenges on reducing location estimation error and cost of localization algorithm itself. For a large mobile network localization cost becomes increasingly important due to the exponential increment of algorithmic cost. Conversely, sacrificing localization accuracy to a great extent is not acceptable at all. To address the localization problem of wireless sensor network this paper presents a novel algorithm based on cross-entropy (CE) method. The proposed centralized algorithm estimates location information of the nodes based on the measured distances of the neighboring nodes. The algorithm minimizes the estimated location error by using CE method. Simulation results compare the proposed CE approach with DV-Hop and simulated annealing (SA)-based localizations and show that this approach provides a balance between the accuracy and cost.

Designing an Application-Aware Routing Protocol for Wireless Sensor Networks

Routing protocols that can facilitate application- specific service guarantee in wireless sensor networks (WSN) constitute one of the key design objectives of current WSN research. Since energy-efficient routing protocols in literature do not offer a complete framework for service differentiation, a newer approach is warranted. Formulating such routing approach requires the adoption of different cost metrics that can parameterize the application-specific requirements. To this effect, this paper proposes an application-aware routing protocol (AARP) that considers battery power, data transaction reliability and end-to-end delay for service differentiation. Two mathematical models namely analytical hierarchical process (AHP) and grey relational analysis (GRA) are incorporated for intermediate node selection (ranking and subsequent selection based on local weight calculation) for data transaction purposes. As demonstrated by the simulation results, the proposed routing approach offers service configurability across a range of applications.

Real-time routing protocols for (m,k)-firm streams based on multi-criteria in wireless sensor networks

Even though some velocity based routing protocols for (m,k)-firm stream have been recently proposed in multimedia wireless sensor networks, there are still many perspective parameters to be considered for forwarding procedure. Moreover, since they are not correlated with each other, multi-criteria system for forwarding is desirable to select next hop. However, current existing protocols apply these parameters sequentially without any prioritization. To address this issue, in this paper, we propose two (m,k)-firm specific routing protocols based on fuzzy interference system and analytical hierarchical process in conjunction with the gray relational analysis. In each protocol, delivery ratio, energy, speed, (m,k)-firm stream requirement as well as current stream status are used to select the best appropriate next hop while considering given node’s constraints. Through the simulation results, we demonstrate that the proposed scheme gracefully maintains (m,k)-firm requirement while extending the network lifetime. Finally, superiority of the proposed approach to existing velocity based routing protocols is also proven through diverse simulation scenarios.

Constrained cross entropy localization technique for wireless sensor networks

Challenges in wireless sensor networks (WSNs) localization are diverse. Addressing the challenges in cross entropy (CE) localization utilizing cross entropy optimization technique in turn minimizes the localization error with a reasonable processing cost and provides a balance between the algorithmic runtime and error. The drawback of such minimization commonly known as flip phenomenon introduces errors in the derived locations. Beyond CE, the whole class of localization techniques utilizing the same cost function suffers from the same phenomenon. This paper introduces constrained cross entropy (CCE), which enhances the localization accuracy by penalizing the identified sensor nodes affected by the aforementioned flip phenomenon in the neighborhood through neighbor sets. Simulation results comparing CCE with both simulated annealing- (SA-) based and original CE localization techniques demonstrate CCEs superiority in a consistent and reliable manner under various circumstances thereby justifing the proposed localization technique.

Simultaneous Perturbation Stochastic Approximation-Based Localization Algorithms for Mobile Devices

Localization precision remains active and open challenge in the area of wireless networks. For static network we develop model free approach of localization technique that by-passes the tedious modeling of diverse aspects to the contributing factor of localization errors, namely simultaneous perturbation stochastic approximation (SPSA) localization technique. The improved version of SPSA, simultaneous perturbation stochastic approximation by neighbor confidence (SPSA-NC) addresses error propagation of iterative localization controlled by incorporating a neighbor confidence matrix. The centralized SPSA and SPSA-NC does not scale well for the mobile environment due to the messaging requirements of repeated updates. We take distributed approaches to implement the aforementioned localization techniques for mobile devices by distributed simultaneous perturbation stochastic approximation (DSPSA) and distributed simultaneous perturbation stochastic approximation by neighbor confidence (DSPSA-NC) respectively, compare the results with the centroid (C) and weighted centroid (WC) localization techniques and show superiority of our methods.

Bacterial Foraging-based Power Allocation for Cooperative Wireless Sensor Networks

Cooperative communication becomes a popular area of research due to its strength and wide application scope in wireless networking and communications. This technique improves the communication performance largely in capacity enhancement, energy-efficiency, timeliness and contention. Power allocation plays an important role in the cooperative communication paradigm to get the desired performance improvements in the aforementioned aspects. In this paper, we present a bacterial foraging optimization algorithm (BFOA)-based power allocation method for cooperative communications in wireless systems. Comparative measures with non-cooperative approaches are made to justify our proposed method.