JPN1406 Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor Networks
- 1. Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor Networks ABSTRACT: Data collection is a common operation of Wireless Sensor Networks (WSNs), of which the performance can be measured by its achievable network capacity. Most existing works studying the network capacity issue are based on the unpractical model called deterministic network model. In this paper, a more reasonable model, probabilistic network model, is considered. For snapshot data collection, we propose a novel Cell-based Path Scheduling (CPS) algorithm that achieves capacity of Ω(1/ 5ω ln n·W) in the sense of the worst case and order-optimal capacity in the sense of expectation, where n is the number of sensor nodes, ω is a constant, and W is the data transmitting rate. For continuous data collection, we propose a Zone-based Pipeline Scheduling (ZPS) algorithm. ZPS significantly speeds up the continuous data collection process by forming a data transmission pipeline, and achieves a capacity gain of N√n/√(log n) ln n or n/log n ln n times better than the optimal capacity of the snapshot data collection scenario in order in the sense of the worst case, where N is the number of snapshots in a continuous data collection task. The simulation results also validate that the proposed
- 2. algorithms significantly improve network capacity compared with the existing works. EXISTING SYSTEM: In deterministic network model, where any pair of nodes in a network is either connected or disconnected. If two nodes are connected, i.e., there is a deterministic link between them, then a successful data transmission can be guaranteed as long as there is no collision. DISADVANTAGES OF EXISTING SYSTEM: Deterministic network model assumption is not practical due to the “transitional region phenomenon”. Recently, many efforts have been spent on the data collection issue. In some tree-based data collection algorithms are proposed under the deterministic network model. PROPOSED SYSTEM: In this paper, the achievable network capacity of SDC.
- 3. First, we propose a novel CPS algorithm for SDC. Subsequently, we analyze the achievable network capacity of CPS. Finally, we make some further discussion about the extension from SDC to CDC ADVANTAGES OF PROPOSED SYSTEM: To evaluate network performance, network capacity, which can reflect the achievable data transmission/collection rate, is usually used. Data collection capacity reflects how fast data have been collected at the sink. ALGORITHM USED: Cell-based Path Scheduling (CPS) algorithm
- 4. SYSTEM ARCHITECTURE: SYSTEM REQUIREMENTS: HARDWARE REQUIREMENTS: System : Pentium IV 2.4 GHz. Hard Disk : 40 GB.
- 5. Floppy Drive : 1.44 Mb. Monitor : 15 VGA Colour. Mouse : Logitech. Ram : 512 Mb. SOFTWARE REQUIREMENTS: Operating system : Windows XP/7/LINUX. Implementation : NS2 NS2 Version : NS2.2.28 Front End : OTCL (Object Oriented Tool Command Language) Tool : Cygwin (To simulate in Windows OS) REFERENCE: Shouling Ji, Raheem Beyah, and Zhipeng Cai, “Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor Networks,” IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 3, MARCH 2014.