Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading in Wireless Sensor Networks

Mobile Data Gathering with Load Balanced Clustering and Dual Data

Uploading in Wireless Sensor Networks

Abstract:

In this paper, a three-layer framework is proposed for mobile data collection in wireless sensor networks, which includes the sensor layer, cluster head layer, and mobile collector (called SenCar) layer. The framework employs distributed load balanced clustering and dual data uploading, which is referred to as LBC-DDU. The objective is to achieve good scalability, long network lifetime and low data collection latency.

At the sensor layer, a distributed load balanced clustering (LBC) algorithm is proposed for sensors to self-organize themselves into clusters. In contrast to existing clustering methods, our scheme generates multiple cluster

heads in each cluster to balance the work load and facilitate dual data uploading. At the cluster head layer, the inter-cluster transmission range is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy- saving inter-cluster communications. Through intercluster transmissions, cluster head information is forwarded to SenCar for its moving trajectory planning. At the mobile collector layer, SenCar is equipped with two antennas, which enables two cluster heads to simultaneously upload data

to SenCar in each time by utilizing multi-user multiple-input and multiple-

output (MU-MIMO) technique. The trajectory planning for SenCar is optimized to fully utilize dual data uploading capability by properly selecting polling points in each cluster. By visiting each selected polling point, SenCar can efficiently gather data from cluster heads and transport the data to the static data sink. Extensive simulations are conducted to evaluate the effectiveness of the proposed LBC-DDU scheme. The results show that when each cluster has at most two cluster heads, LBC-DDU achieves over 50% energy saving per node and 60% energy saving on cluster heads comparing with data collection through multi-hop relay to the static data sink, and 20% shorter data collection time compared to traditional mobile data gathering.

Existing System:

Sensors are generally densely deployed and randomly scattered over a sensing field and left unattended after being deployed, which makes it difficult to recharge or replace their batteries. After sensors form into autonomous organizations, those sensors near the data sink typically deplete their batteries much faster than others due to more relaying traffic. When sensors around the data sink deplete their energy, network connectivity and coverage may not be guaranteed.

Due to these constraints, it is crucial to design an energy-efficient data collection scheme that consumes energy uniformly across the sensing field to achieve long network lifetime. Furthermore, as sensing data in some applications are time-sensitive, data collection may be required to be performed within a specified time frame. Therefore, an efficient, large-scale

data collection scheme should aim at good scalability, long network

lifetime and low data latency.

Proposed System:

First, we propose a distributed algorithm to organize sensors into clusters, where each cluster has multiple cluster heads. In contrast to clustering techniques proposed in previous works, our algorithm balances the load of intra-cluster aggregation and enables dual data uploading between multiple cluster heads and the mobile collector.

Second, multiple cluster heads within a cluster can collaborate with each other to perform energy-efficient inter cluster transmissions. Different from other hierarchical schemes, in our algorithm, cluster heads do not relay

data packets from other clusters, which effectively alleviates the burden of

each cluster head.

Instead, forwarding paths among clusters are only used to route small- sized identification (ID) information of cluster heads to the mobile collector for optimizing the data collection tour.

Third, we deploy a mobile collector with two antennas (called SenCar in this paper) to allow concurrent uploading from two cluster heads by using MU-MIMO communication.

Hardware Requirements:

•       System              : Pentium IV 2.4 GHz.

•       Hard Disk        : 40 GB.

•       Floppy Drive   : 1.44 Mb.

•       Monitor            : 15 VGA Colour.

•       Mouse               : Logitech.

•       RAM                 : 256 Mb.

Software Requirements:

•       Operating system    : - Windows XP.

•       Front End                  : - JSP

•       Back End                   : - SQL Server

Software Requirements:

•       Operating system    : - Windows XP.

•       Front End                  : - .Net

•       Back End                   : - SQL Server