An Algorithmic approach for Localization using Single Mobile Anchor Node using Information Baton Handover Policy

The main goal of a sensor network is to collect and forward data to destination. It is very essential to know about the location of collected data. This type of information can be obtained using localization technique in wireless sensor networks (WSNs). Localization is a technique to determine the location of sensor nodes. Many research and work around is carried on Localization technique in WSN, because of its huge application in day today life. It is very important to design a low-cost, scalable, and efficient localization mechanisms for WSNs

Application of rasch model on resilience in higher education: an examination of validity and reliability of Malaysian academician happiness index (MAHI)

This preliminary study was conducted to examine and verify the validity and reliability of the instrument on the Malaysian Academician Happiness Index (MAHI) on resilience. MAHI could be seen as a tool to measure the level of happiness and stress of academicians before determining how resilient the academicians were. Resilience can be defined as a mental ability of a person to recover quickly from illness or depression. MAHI instrument consisted of 66 items. The instrument was distributed to 40 academicians from three groups of universities which were the Focus University, Comprehensive University and Research University is using a survey technique. The instrument was developed to measure three main constructs which were the organization, individual and social that would affect the happiness and stress levels of academicians. This preliminary study employed the Rasch Measurement Model uses Winsteps software version 3.69.1.11. to examine the validity and reliability of the items. The results of the analysis of the MAHI instrument showed that the item reliability was 0.87, person reliability was 0.83 and value of Alpha Cronbach was 0.84. Meanwhile, misfit analysis showed that only there was one item with 1.46 logit that could be considered for dropping or needed improvement. Therefore, it highlighted that most of the items met the constructs’ need and can be used as a measurement indicator of MAHI. The implication of this instrument can help Malaysian academicians to be more resilient in facing challenges in the future

An Efficient and Self-Adapting Localization in Static Wireless Sensor Networks

Localization is one of the most important subjects in Wireless Sensor Networks (WSNs). To reduce the number of beacons and adopt probabilistic methods, some particle filter-based mobile beacon-assisted localization approaches have been proposed, such as Mobile Beacon-assisted Localization (MBL), Adapting MBL (A-MBL), and the method proposed by Hang et al. Some new significant problems arise in these approaches, however. The first question is which probability distribution should be selected as the dynamic model in the prediction stage. The second is whether the unknown node adopts neighbors’ observation in the update stage. The third is how to find a self-adapting mechanism to achieve more flexibility in the adapting stage. In this paper, we give the theoretical analysis and experimental evaluations to suggest which probability distribution in the dynamic model should be adopted to improve the efficiency in the prediction stage. We also give the condition for whether the unknown node should use the observations from its neighbors to improve the accuracy. Finally, we propose a Self-Adapting Mobile Beacon-assisted Localization (SA-MBL) approach to achieve more flexibility and achieve almost the same performance with A-MBL

Adapting Mobile Beacon-Assisted Localization in Wireless Sensor Networks

The ability to automatically locate sensor nodes is essential in many Wireless Sensor Network (WSN) applications. To reduce the number of beacons, many mobile-assisted approaches have been proposed. Current mobile-assisted approaches for localization require special hardware or belong to centralized localization algorithms involving some deterministic approaches due to the fact that they explicitly consider the impreciseness of location estimates. In this paper, we first propose a range-free, distributed and probabilistic Mobile Beacon-assisted Localization (MBL) approach for static WSNs. Then, we propose another approach based on MBL, called Adapting MBL (A-MBL), to increase the efficiency and accuracy of MBL by adapting the size of sample sets and the parameter of the dynamic model during the estimation process. Evaluation results show that the accuracy of MBL and A-MBL outperform both Mobile and Static sensor network Localization (MSL) and Arrival and Departure Overlap (ADO) when both of them use only a single mobile beacon for localization in static WSNs

Demand-driven movement strategy for moving beacons in distributed sensor localization

n a wireless sensor network, range-free localization with a moving beacon can reduce susceptibility to communication noises while concomitantly eliminate need for large number of expensive anchor nodes that are vulnerable to malicious attacks. This paper presents a moving beacon aided range-free localization technique, which is capable of estimating the location of a sensor with high accuracy. A novel distributed localization scheme is designed to optimally determine beacon movement strategy according to user demand. Superiority of this scheme to the state-of-the-art has been established in terms of location estimation quality, measured by the theoretical expected maximum error and simulated mean error while optimizing the beacon location density or traversal path length

A Walking Beacon-Assisted Localization in Wireless Sensor Networks

Abstract—The localization of the sensor node is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from a GPS device or by virtue of being manually placed. In this paper, we propose two distributed methods to localization of sensor nodes using a single moving beacon where sensor nodes compute their position estimate based on the range-free technique. The first method uses the arrival and departure information of a walking beacon and the second method exploits the variance of the Received Signal Strength (RSS) from the beacon. We provide the upper bound of the estimation error for these methods in an ideal environment. Critical to the location accuracy of sensor nodes are two more parameters, the radio transmission range of the beacon, and how often the beacon broadcasts its position. Simulation results show the location estimate error of sensor nodes applying the proposed two methods. The results are consistent to the theoretical analysis and the average estimate errors could be within one meter. I