Computing localized power efficient data


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Computing Localized Power-Efficient Data Aggregation Trees
For Sensor Networks

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Computing localized power efficient data

  1. 1. Ambitlick Solutions Computing Localized Power-Efficient Data Aggregation Trees For Sensor NetworksAbstract: We propose localized, self organizing, robust, and energy-efficient dataaggregation tree approaches for sensor networks, which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They are based on topologies,such as LMST and RNG, that can approximate minimum spanning tree and can beefficiently computed using only position or distance information of one-hopneighbors. The actual routing tree is constructed over these topologies. We alsoconsider different parent selection strategies while constructing a routing tree. Wecompare each topology and parent selection strategy and conclude that the bestamong them is the shortest path strategy over LMST structure. Our solution alsoinvolves route maintenance procedures that will be executed when a sensor nodefails or a new node is added to the network. The proposed solution is also adaptedto consider the remaining power levels of nodes in order to increase the networklifetime. Our simulation results show that by using our power-aware localizedapproach, we can almost have the same performance of a centralized solution interms of network lifetime, and close to 90 percent of an upper bound derived here.
  2. 2. Ambitlick SolutionsSYSTEM ANALYSES :Problem Definition: The problem is to find an energy-efficient routing plan which maximizes thenetwork lifetime. The routing plan determines for each node the incoming andoutgoing neighbors for data forwarding and aggregation. In other words, a treespanning all the nodes must be found as the routing plan. The routing schemeshould also include mechanisms to handle node failures and support new nodearrivals.Existing System: The minimum spanning tree (MST)-based routing provides goodperformance in terms of lifetime when the data are gathered using aggregation incentralized manner alone.Proposed System: 1. Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs) 2. The routing tree is constructed over LMST and RNG topologies. 3. Route maintenance. 4. Data aggregation protocol (LEACH protocol-Self-configuring Clusters) 5. To minimize Setup cost and maintenance cost
  3. 3. Ambitlick SolutionsLiterature Review:1. A QoS Routing for Maximum Bandwidth in Ad Hoc Networks: Ad hoc networks have characteristics such as flexibility, fast and easydeployment, robustness which make them an interesting technology for variousapplications. Ad hoc networks are considered as the most promising terminalnetworks in future mobile communications. Providing sufficient bandwidth formultimedia applications in ad hoc networks is an urgent task because of the risingpopularity of multimedia applications and potential commercial usage of ad hocnetworks. Bandwidth is more difficult to guarantee in ad hoc networks than inother types of networks, and providing end-to-end bandwidth guarantee is a criticaland challenging problem in ad hoc networks because of multihop, mutual radiointerference and node mobility. A bandwidth-aware routing protocol of BARP,which is based on the existing Dynamic Source Routing protocol (DSR), isproposed in this paper in order to find a route of approximately maximumbandwidth for a flow from a source node to a destination node in a wireless ad hocnetwork. BARP is a novel bandwidth-aware routing protocol by which a route oflargest bandwidth can be found. This routing protocol takes advantage of largerbandwidth than the existing work, and its effectiveness is demonstrated by some
  4. 4. Ambitlick Solutionssimulations. It will be a great contribution to end-to-end QoS support research inwireless ad hoc networks.2. Power Efficient Data Gathering and Aggregation in Wireless Sensor Networks: Energy efficiency is an important design criterion for the development ofsensor networking protocols involving data dissemination and gathering. In-network processing of sensor data, aggregation, transmission power control inradios, and periodic cycling of node wake-up schedules are some techniques thathave been proposed in the sensor networking literature for achieving energyefficiency. Owing to the broadcast nature of the wireless channel many nodes inthe vicinity of a sender node may overhear its packet transmissions even if they arenot the intended recipients of these transmissions. Reception of these transmissionscan result in unnecessary expenditure of battery energy of the recipients. Weinvestigate the impact of overhearing transmissions on total energy costs duringdata gathering and dissemination and attempt to minimize them systematically. Wemodel the minimum energy data gathering problem as a directed minimum energyspanning tree problem where the energy cost of each edge in the wirelessconnectivity graph is augmented by the overhearing cost of the correspondingtransmission. We observe that in dense sensor networks, overhearing costs
  5. 5. Ambitlick Solutionsconstitute a significant fraction of the total energy cost and that computing theminimum spanning tree on the augmented cost metric results in energy savings,especially in networks with non-uniform spatial node distribution. We also studythe impact of this new metric on the well known energy-efficient dissemination(also called broadcasting) algorithms for multihop wireless networks. We show viasimulation that through this augmented cost metric, gains in energy efficiency of10% or more are possible without additional hardware and minimal additionalcomplexity.3. Establishment of survivable connections in WDM networks using partial pathprotection: As a generalization of the traditional path protection scheme in WDMnetworks where a backup path is needed for each active path, the partial pathprotection scheme uses a collection of backup paths to protect an active path,where each backup path in the collection protects one or more links on the activepath such that every link on the active path is protected by one of the backup paths.While there is no known polynomial time algorithm for computing an active pathand a corresponding backup path using the path protection scheme for a source-destination node pair, we show that an active path and a corresponding collection
  6. 6. Ambitlick Solutionsof backup paths using the partial path protection scheme can be computed inpolynomial time, whenever they exist, under each of the following two networkmodels: (a) dedicated protection in WDM networks without wavelengthconverters; and (b) shared protection in WDM networks without wavelengthconverters. Under each of the two models, we prove, that for any given source sand destination d in the network, if one candidate active path connecting s and d isprotectable using partial path protection, then any candidate active path connectings and d is also protectable using partial path protection. This fundamental propertyleads to efficient shortest active path algorithms that can find an active path and itscorresponding partial path protections whenever they exist. Simulation resultsshow that shared partial path protection outperforms shared path protection interms of blocking probability.