Convectional Omni directional sensors that always have an omni angle of sensing range, directional sensors may have a limited angle of sensing range due to the technical constraints or cost considerations. A directional sensor network consists of a number of directional sensors, which can switch to several directions to extend their sensing ability to cover all the targets in a given area. Improving the energy efficiency is still an important issue. This paper solves the

Wireless Sensor Network is an major emerging technique in wireless communication technology for application across a wide array of domains such as the military surveillance, medical diagnosis, weather forecasting, fire detection alarming systems, etc. One of the main challenges of wireless sensor network (WSN) is how to improve its time of livelihood due to the restricted energy of sensor nodes. Data must be aggregated in order to avoid amounts of traffic in the network, limit the recourses and energy. To solve the above dilemmas , data mining process such as clustering and data aggregation is used . clustering is used to group the nodes where as data aggregation function like MIN,MAX,AVG is used for swabbing redundant data transmission and improves the life span of energy in wireless sensor network. In this paper a new approach related to Voronoi based Genetic clustering (VBGC) Algorithm is proposed for energy efficient data aggregation. Our algorithm achieves energy efficiency by reducing the number of data transmission in each round to cluster head and from it to Base station (BS) . The Base Station periodically executes the proposed algorithm to select new Cluster-Heads after a certain period of time. Simulation results reveal that our algorithm outperforms basic GA.

In precise, Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, smart and inexpensive sensors resulting in cost effective and easily deployable WSNs. However, analysers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this study, we give an overview of wireless sensor networks and their application domains including the challenges that should be

Finding cluster head (CH) is an important issue in WSN. A new optimization algorithm Imperialist Competitive Algorithm (ICA) has been introduced recently, inspired by socio-political process of imperialistic competition. We use ICA for CH selection according to the communication energy (CE) cost. We demonstrate that ICA is an effective method for selection of CH in WSN. ICA either finds one or at most a few CHs within 500 decades. The tie is broken by use of a heuristic. CE stabilizes after 225 decades in the case of 300size, after 150 decades for 200-size, and after 140 decades for 100-size WSNs. For 100-size, 1 CH is selected after 260 decades, for 200-size and 300-size 7 and 21 CHs, respectively are selected after 500 decades. For reducing the number of final CHs, the algorithm should be run for more than 500 decades for larger-size WSNs. For smaller size (100) networks, time increases very slowly with decades. For higher size networks, it increases nonlinearly and takes almost exponential shape with a network of 300 sensors. This is a preliminary study and we plan further investigation in this direction.

In the past years, Wireless Sensor Networks (WSNs) have gained increasing attention from both the users and researchers. It is used in various fields which include environmental, healthcare, military and other commercial applications. Sensor nodes are battery powered so energy constraints on nodes are very strict. When battery gets discharged, sensor node will get disconnected from remaining network. This results in link failure and data loss. In some applications battery replacement is also not possible. Hence energy efficient techniques should be designed which will enhance lifetime of network and accurate data transfer. In this paper, different sources of energy dissipation are listed followed by energy efficient techniques to enhance lifetime of the network.

The concept behind secure data collection using randomized dispersive routes used for preventing compromised node and denial of service attacks. These two attacks are familiar for generating black holes during passive interception and information block delivery. A randomized path delivery for secure and reliable data collection in wireless sensor networks was designed to generate highly randomized dispersive routes at low energy cost and by reducing the unnecessary retransmissions and improve energy efficiency. Besides randomness, the generated routes are evolved using two propagation techniques NRRP & DRP so as to achieve energy consumption under given security constraints without generating extra copies of secret shares. In this paper, we propose to implement cloud platform, a third party onsite (TPO) and a third party field (TPF). Afore said proposal shall increase the agility of the concept and shall eliminate the drawbacks of existing concept.

Least Square Policy Iteration (LSPI) is a model-free Reinforcement Learning algorithm capable of dealing with continuous states and actions. Chebyshev polynomials are utilized as the approximator in LSPI while Kalman Filtering handles sampled, corrupted and delayed data. Since LSPI solves optimal problems, the algorithm needs to have an exploration phase in order to avoid local minima and to cope with non-stationary cost-to-go functions. The chapter investigates how often information between neighbors in cooperative Multi-Agent Systems (MAS) needs to be exchanged in order to meet a desired performance. It suggests that stabilizing upper bounds for intervals between two consecutive broadcasting instants of each individual agent, thereby giving rise to asynchronous communication. It analyses the optimal intermittent feedback problem for MASs. The chapter explains the optimal intermittent feedback …

This correspondence presents two variable-rate encoding algorithms that achieve capacity for the (d,k) constraint when k=2d+1, or when k-d+1 is not prime. The first algorithm, symbol sliding, is a generalized version of the bit flipping algorithm introduced by Aviran In addition to achieving capacity for (d,2d+1) constraints, it comes close to capacity in other cases. The second algorithm is based on interleaving and is a generalized version of the bit stuffing algorithm introduced by Bender and Wolf. This method uses fewer than k-d biased bit streams to achieve capacity for (d,k) constraints with k-d+1 not prime. In particular, the encoder for (d,d+2/sup m/-1) constraints 2 /spl les/ m < /spl infin/ requires only m biased bit streams.

Recent years have seen tremendous growth in the deployment of wireless local area networks (WLANs). An important design issue in such networks is that of distributed scheduling. The lack of centralized control leads to multiple users competing for channel access. This leads to significant throughput degradation. Existing approaches, such as the slotted Aloha protocol and IEEE 802.11 DCF, also fail to provide differentiated service to users. The upcoming IEEE 802.11e enhanced DCF incorporates additional mechanisms to provide support for service differentiation. However, the level of differentiation achieved with these mechanisms is difficult to quantify. In this paper, we propose a class of distributed scheduling algorithms, regulated contention medium access control (RCMAC), which provides dynamic prioritized access to users for service differentiation in a quantifiable manner. Furthermore, by regulating multi-user contention, RCMAC achieves higher throughput when traffic is bursty, as is typically the case. In addition to WLANs, the basic concepts of RCMAC have applications in ad hoc networks and emerging sensor networks.

This paper considers the problem of capacity equivalence for a general class of (M,d,k) run-length-limited constraints, namely we look for pairs (M,d,k) and (M',d',k') that have the same capacity. Our approach is based on a time domain interpretation where the characteristic (M,d,k) polynomial is viewed as an impulse train and factorization is related to convolution in discrete time. Using this interpretation, we first derive the known binary equivalence relations and then generalize to the M-ary case.

A class of distributed scheduling algorithms, Regulated Contention Medium Access Control (RCMAC), which provides dynamic prioritized access to users for service differentiation, is considered in this paper. In addition to WLANs, the basic concepts of RCMAC have applications in multihop cellular and ad hoc networks and emerging sensor networks. Furthermore, by regulating multiuser contention, RCMAC achieves higher throughput when traffic is bursty. In this paper, differential function with two special cases like weight proportional and old base regulation is presented. Arrivals at each user are bursty, generated using standard two-state Markov model and the multiplicative increase/decrease rule are employed.

This paper addresses the question of optimal packet size for data communication in energy constrained wireless sensor networks. Unlike previous work on packet length optimization in other wired and wireless networks, energy efficiency is chosen as the optimization metric. The use of fixed size packets is proposed in light of the limited resources and management costs in sensor networks. The optimal fixed packet size is then determined for a set of radio and channel parameters by maximizing the energy efficiency metric. Further, the effect of error control on packet size optimization and energy efficiency is examined. While retransmission schemes are found to be energy inefficient, it is shown that forward error correction can improve the energy efficiency eventhough it introduces additional parity bits and encoding/decoding energy consumptions. In this regard, binary BCH codes are found to be 15% more energy efficient than the best performing convolutional codes, which have thus far been considered for error control in sensor networks.

This paper describes the concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics. First, the sensing tasks and the potential sensor networks applications are explored, and a review of factors influencing the design of sensor networks is provided. Then, the communication architecture for sensor networks is outlined, and the algorithms and protocols developed for each layer in the literature are explored. Open research issues for the realization of sensor networks are also discussed.

Node capture is a severe threat to data security in Wireless Sensor Networks(WSNs). This paper aimed to design an enhanced and efficient scheme against node capture attack using hash-chain in wireless sensor networks. Key management is the fundamental security mechanism in wireless sensor networks, but existing schemes based on probability have poor resistance to node capture attack. In order to improve the resilience against node capture attack, a hash-chain based scheme to resist node capture attack was presented. The main idea of the proposed consisted of applying a hash function on the initial preloaded keys before deployment. During the key pre-distribution, the selected keys were hashed according to certain rules and the hashed results were as communication key. Theoretical analysis and simulation results show that, key exposal probability and average insecure degree decrease by 56 and …

The advancement in wireless communications and electronics has enabled the development of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments in this field.