• D.J Samatha Naidu
• N.Reshma Chandrika
• C.Sasidhar

Several different approaches have been proposed to significantly reduce the energy cost of WSNs by using the mobility of nodes. The network can collect data from static nodes through one-hop or multi-hop transmissions. The mobile node may serve as the base station or a “data mule” that transports data between static nodes and the base station. Mobile nodes may also be used as relays that forward data from source nodes to the base station. Several movement strategies for mobile relays have been studied. In existing work, the effectiveness of mobility in energy conservation is demonstrated by previous studies, the following key issues have not been collectively addressed. First, the movement cost of mobile nodes is not accounted for in the total network energy consumption. Instead, mobile nodes are often assumed to have replenished able energy supplies which are not always feasible due to the constraints of the physical environment. Second, complex motion planning of mobile nodes is often assumed in existing solutions which introduces significant design complexity and manufacturing costs. In mobile nodes need to repeatedly compute optimal motion paths and change their location, their orientation and/or speed of movement. Such capabilities are usually not supported by existing low-cost mobile sensor platforms. Third Robomote nodes are designed using 8-bit CPUs and small batteries that only last for about 25 minutes in full motion. In proposed work, to minimize the total energy consumed by both mobility of relay nodes and wireless transmissions. Most previous work ignored the energy consumed by moving mobile relays. The proposed model both sources of energy consumption, the optimal position of a node that receives data from one or multiple neighbors and transmits it to a single parent is not the midpoint of its neighbors; instead, it converges to this position as the amount of data transmitted goes to infinity, and consider the optimal initial routing tree in a static environment where no nodes can move. However, the proposed approach can work with less optimal initial configurations including one generated using only local information such as greedy geographic routing. It improves the initial configuration using two iterative schemes. The first inserts new nodes into the tree. The second computes the optimal positions of relay nodes in the tree given a fixed topology. This algorithm can reduce data-intensive wireless sensor networks. It allows some nodes to move while others do not because any local improvement for a given mobile relay is a global improvement. This allows us to potentially extend with proposed approach to handle additional constraints on individual nodes such as low energy levels or mobility restrictions due to application requirements. Finally it can be implemented in a centralized or distributed fashion. In proposed work, the following contributions in this project (1). To formulate the problem of Optimal Mobile Relay Configuration (OMRC) in data-intensive WSNs. The objective of energy conservation is holistic in that the total energy consumed by both mobility of relays and wireless transmissions is minimized, which is in contrast to existing mobility approaches that only minimize the transmission energy consumption. The energy consumption between mobility and transmission is exploited by configuring the positions of mobile relays. (2) The study can effect of the initial configuration on the final result. It compare different initial tree building strategies and propose an optimal tree construction strategy for static nodes with no mobility. (3) To develop two algorithms that iteratively refines the configuration of mobile relays. The first improves the tree topology by adding new nodes. It is not guaranteed to find the optimal topology. The second improves the routing tree by relocating nodes without changing the tree topology. It converges to the optimal node positions for the given topology. (4) To conduct extensive simulations based on realistic energy models obtained from existing mobile and static sensor platforms. The framework consists of three main algorithms. The first algorithm computes an optimal routing tree assuming no nodes can move. The second algorithm improves the topology of the routing tree by greedily adding new nodes exploiting mobility of the newly added nodes. The third algorithm improves the routing tree by relocating its nodes without changing its topology. This iterative algorithm converges on the optimal position for each node given the constraint that the routing tree topology does not change. It presents efficient distributed implementations for each algorithm that require only limited, localized synchronization.

Introduction, related work, data intensive problems, wireless sensor networks

"REDUCING DATA-INTENSIVE PROBLEMS IN WIRELESS SENSOR NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.161-166, May-2019, Available :http://www.jetir.org/papers/JETIRBR06033.pdf

"REDUCING DATA-INTENSIVE PROBLEMS IN WIRELESS SENSOR NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp161-166, May-2019, Available at : http://www.jetir.org/papers/JETIRBR06033.pdf