Efficient Actor Recovery Paradigm For Wireless Sensor And Actor Networks

Wireless sensor networks (WSNs) are becoming widely used worldwide. Wireless Sensor and Actor Networks (WSANs) represent a special category of WSNs wherein actors and sensors collaborate to perform specific tasks. WSANs have become one of the most preeminent emerging type of WSNs. Sensors with nodes having limited power resources are responsible for sensing and transmitting events to actor nodes. Actors are high-performance nodes equipped with rich resources that have the ability to collect, process, transmit data and perform various actions. WSANs have a unique architecture that distinguishes them from WSNs. Due to the characteristics of WSANs, numerous challenges arise. Determining the importance of factors usually depends on the application requirements. The actor nodes are the spine of WSANs that collaborate to perform the specific tasks in an unsubstantiated and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power fatigue of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. It is essential to keep inter-actor connectivity in order to insure network connectivity. Thus, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). For network recovery process from actor node failure, optimal re-localization and coordination techniques should take place. In this work, we propose an efficient actor recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balances the network performance. The packet is handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets (Either from actor or sensor). This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, we compare the performance of our proposed work with state-of the art localization algorithms. Our experimental results show superior performance in regards to network life, residual energy, reliability, sensor/ actor recovery time and data recovery

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.https://doi.org/10.3390/s1704085

An Energy Efficient Simultaneous-Node Repositioning Algorithm for Mobile Sensor Networks

Recently, wireless sensor network (WSN) applications have seen an increase in interest. In search and rescue, battlefield reconnaissance, and some other such applications, so that a survey of the area of interest can be made collectively, a set of mobile nodes is deployed. Keeping the network nodes connected is vital for WSNs to be effective. The provision of connectivity can be made at the time of startup and can be maintained by carefully coordinating the nodes when they move. However, if a node suddenly fails, the network could be partitioned to cause communication problems. Recently, several methods that use the relocation of nodes for connectivity restoration have been proposed. However, these methods have the tendency to not consider the potential coverage loss in some locations. This paper addresses the concerns of both connectivity and coverage in an integrated way so that this gap can be filled. A novel algorithm for simultaneous-node repositioning is introduced. In this approach, each neighbour of the failed node, one by one, moves in for a certain amount of time to take the place of the failed node, after which it returns to its original location in the network. The effectiveness of this algorithm has been verified by the simulation results

A Comparison between RISC and CISC Microprocessor Architectures

- In this paper, we have made a comparison between RISC (Reduced Instruction Set Computer) and CISC (Complex Instruction Set Computer.) RISC and CISC are two different types of microprocessor architectures. RISC is a computer microprocessor that uses simple instructions which can be divided into multiple instructions that performs low level operations within a single clock cycle while CISC is a PC processor which utilizes single direction to execute a few low level operations, for example, stacking from memory, a number juggling operation, and a memory store or are fit for multi-step operations or tending to modes inside single guideline. The principle distinction amongst RISC and CISC is in the quantity of figuring cycles each of their directions take. The distinction in the quantity of cycles depends on the intricacy and the objective of their directions

An Overview of 5G Wireless Networks- Past, Present and Future

5G stands for fifth generation mobiles. Fromgeneration 1G to 2.5G and from 3G to 5G this world of telecommunication got improvement along with improve performance with every passing day. Due to this rapid improvement the world become like a little village where we can interact, work, learn and spread our knowledge etc. over the world. This improvement makes our daily life so much easy.By 2020 all networks will support voice, videoand a complex range of communication services for more 9 billion users and billions of connected Around the same time the next generation 5G of telecom technology, equipment and devices will become commercially available.It is the next generation of telecom networks designed to meet a more advanced and complex set of performance requirement. It represents new way of thinking. The main purpose of 5G networks is that, user can simultaneously connect to multiple wireless technologies and can switch between them.5G will offer the service like Documentations, Supporting electronic transmissions such as e-payment-transaction

An Overview of 4G LTE Technologies – A Top down Approach

4G LTE design began in 2000 and was first implemented in 2010.commercially in DLTE technology introduced December 2009 by teliasonerain Norway and Sweden came to the U.S. in 2010.Data rates and supportable bandwidths much higher in Forth generation and This has a significant in fact on voice. In cellular telecommunications, the term handover or handoff refers to the process of transferring an ongoing call or data session from one channel connected to the core network to another channel.In This paper we provide a comprehensive overview of Long Term Evolution network evolution.4G technologies are designed to provide IP-based voice, data and multimedia streaming at speeds of at least 100 Mbit per second and up to as fast as 1 Gbitper second

LOCALIZED MOVEMENT CONTROL CONNECTIVITY RESTORATION ALGORITHMS FOR WIRELESS SENSOR AND ACTOR NETWORKS

Wireless Sensor and Actor Networks (WSANs) are gaining an increased interest because of their suitability for mission-critical applications that require autonomous and intelligent interaction with the environment. Hazardous application environments such as forest fire monitoring, disaster management, search and rescue, homeland security, battlefield reconnaissance, etc. make actors susceptible to physical damage. Failure of a critical (i.e. cut-vertex) actor partitions the inter-actor network into disjointed segments while leaving a coverage hole. Maintaining inter-actor connectivity is extremely important in mission-critical applications of WSANs where actors have to quickly plan an optimal coordinated response to detected events. Some proactive approaches pursued in the literature deploy redundant nodes to provide fault tolerance; however, this necessitates a large actor count that leads to higher cost and becomes impractical. On the other hand, the harsh environment strictly prohibits an external intervention to replace a failed node. Meanwhile, reactive approaches might not be suitable for time-sensitive applications. The autonomous and unattended nature of WSANs necessitates a self-healing and agile recovery process that involves existing actors to mend the severed inter-actor connectivity by reconfiguring the topology. Moreover, though the possibility of simultaneous multiple actor failure is rare, it may be precipitated by a hostile environment and disastrous events. With only localized information, recovery from such failures is extremely challenging. Furthermore, some applications may impose application-level constraints while recovering from a node failure. In this dissertation, we address the challenging connectivity restoration problem while maintaining minimal network state information. We have exploited the controlled movement of existing (internal) actors to restore the lost connectivity while minimizing the impact on coverage. We have pursued distributed greedy heuristics. This dissertation presents four novel approaches for recovering from node failure. In the first approach, volunteer actors exploit their partially utilized transmission power and reposition themselves in such a way that the connectivity is restored. The second approach identifies critical actors in advance, designates them preferably as noncritical backup nodes that replace the failed primary if such contingency arises in the future. In the third approach, we design a distributed algorithm that recovers from a special case of multiple simultaneous failures. The fourth approach factors in application-level constraints on the mobility of actors while recovering from node failure and strives to minimize the impact of critical node failure on coverage and connectivity. The performance of proposed approaches is analyzed and validated through extensive simulations. Simulation results confirm the effectiveness of proposed approaches that outperform the best contemporary schemes found in literature

Long Term Evolution and its Handover Mechanism

LTE technology wascommercially introduced byTeliaSonera in Norway in December2009. The abbreviation of LTE is Long Term Evolution.It is the third generation partnership project(3GPP).It is also developed widely by international organization.LTE is developed to support both the time division duplex technology(TDD) as well as historical information. The Architecture of high level network technology LTE is obtained from the three main point’s 1.The user Equipment, 2.The Evolved UMTS Terrestrial Radio Access Network(E_UTRAN)and 3rd is the (EPC)Evolved PacketCore.Handover mechanism is published to be used in 3GPP LTE in orderto reduce the complexity of LTE Network architecture.The Standards isdeveloped by3GPP and is specie in its release 8 document series, LTE is the natural upgrade path forbid GSM/UMTS networks and CDMA200 networks.A critical task for operators is to plain LTE network layer independently without losing the cooperation