Data management issues

Abstract:

The main goal of this paper reveals that the mobility sinks using for enhancing the life period of the wireless sensor networks with power constrained nodes, which means the network is capable to perform its deliberated functionalities within the period of time. The mobility of data collection sinks moving to the network areas and gathering data from sensors, which means short range communication such as Intelligent Transport Systems(ITS). Our findings prove that by taking importance of the sinks mobility. It's rapidly reduce the energy usage on relaying traffic and to increases the life time of the network.

Introduction

Wireless sensor networks explores the large number of small devices (sensors) with sensing and routing capabilities(1). The mobility of data collection sinks moving to the network areas and gathering data from sensors, which means short range communication such as Intelligent Transportation Systems(ITS). This is the main application scenarios by using sink mobility technique and some cases mobile sink is also using for the long range communication such as satellites, Zigbee, Wi-Fi, Wi-Max, etc. But it is extremely expensive and inefficient(1). The physical activities of nodes providing communication in between the sensor nodes and the network operator, such as heavy vehicles, buses, cars, pedestrians and industrial monitoring etc.

In this work, mobility users sending by query to a WSN, it is used to providing current information on the surrounding environments. For an example Intelligent Transportation Systems(ITS) which means it is monitoring to the status of vehicles and detecting the worst situations on the roads like damages, critical curves(2).

Single-hop routing is developed for transport of the sensor to data collection nodes (3),(4), mainly It is focusing on to increasing the lifetime of the network. There are two mobilities such as fast and slow mobilities for joint sink mobility to extends the network lifetime. Sink can transport the data with its movements enough to produce a tolerable data delivery delay. The Multi-hop routing is implemented to transport the sensed data to sinks, comparing to single-hop routing it is more expensive and high power consumption and the cost of the implementation is high. Sensor networks with mobile sink(MSSN) gets high energy efficiency, because the Multi-hop transmission of high energy data over the network is converted to single-hop transmission. In addition to single-hop routing network gives high security, low cost and ease to implement and it states single node sensor is communicating with the mobile sink on a given network.

Sink Mobility

The mobility of data collection sinks moving to the network areas and gathering the data from sensors. The application scenarios of sink mobilities such as Sink Mobility Protocols

Exploiting sink mobility and Adaptive sink mobility (1).

Sink Mobility Protocols :

This application supports to the information gathering in the presence of mobile querying node that occurs often interruptions from a wireless sensor networks(WSN). It starts to convey the information,when it's queried to a sink node, which gives the gateway towards the mobile sink.

The mobile sinks sending by a query to WSN deployed in the environment. It is providing the real time information on the environment by using the WSN deployment. For an example Intelligent Transportation Systems(ITS). It detects the damages on the road, when car has been moving on the road.

This is the main application scenarios by using sink mobility technique and some cases mobile sink also using for the long range communication such as satellites, Zigbee, Wi-Fi, Wi-Max, industrial monitoring etc. But it is extremely expensive and inefficient(1). The physical activities of nodes providing communication in between the sensor nodes and the network user.

In this consists of three nodes, Mobile Sink(MS), the node is to take the position along the road, Vice Sink(VS), this node is able to performs directly communicate with the MS and Sensor node(SN) performs a query and data forwarding but it can reaches MS through a VS. Mobile sink gives the final destination of the data produced by the WSN. For instances of MS are buses, cars and pedestrians etc. these all examples are applicable for single-hop communications, like detecting weather and traffic conditions.

The application scenario of fig.1 shows the mobile sink gives a query on the WSN through a first vice sink, then it is forwarded to the closest region(highlighted region). The destination node constitutes the information of closest region by querying other nodes,it belongs to the same region and sends received data to the target destination.

Exploiting sink mobility:

The purpose of exploiting sink mobility is using for increasing the life time period of the sensor networks with power constrained nodes. The theme of the function is maximizing the overall network lifetime and minimizing the power consumption in the nodes, which means it describes the time till the first node "dies" because of energy depletion(3),(4).

The Multi-hop routing is implemented to transport the sensed data to sinks, comparing to single-hop routing it is more expensive and high power consumption and the cost of the implementation is high. The Sensor networks with mobile sink(MSSN) gets high energy efficiency, because the Multi-hop transmission of high energy data over the network is converted to single-hop transmission. In addition to single-hop routing network gives high security, low cost and ease to implement(5). The mobile sinks to the sensor fields called as mules, it acts as a forwarding agents ant it works to save the energy by taking single-hop routing instead of that multi-hop routing is more expensive.

Adaptive Sink Mobility :

Energy efficient is a essential part in Wireless Sensor Networks(WSN). It describes a solution to decreasing the energy consumption by adaptively moving the sink node and it takes the event driven scenario, which means it defines a "significant change in state", it may reducing the cluster of activated sensors to the sink node (3). The mobile sink may adapt and nearer to the sensor nodes, it supports delay-sensitive real-time applications and it is able to take position inside of the network.

It has been given as three type of minimizing energy consumption solutions, mainly these techniques are using for single-hop wireless sensor networks such as minimizing average energy consumption, minimizing maximum energy consumption and minimizing relative energy consumption (3). This network delivers the minimal energy to communication between the active cluster heads(CHs) and sink. By using this minimizing maximum energy consumption technique is to overcome this problem (6). It reduces the transmission energy for the cluster remote head in the network. Instead of, the maximum transmission energy is minimized. This transmission energy depends on the distance between the sensor and sink and every cluster head in the network.

CONCLUSION

Wireless sensor networks explores the large number of small devices (sensors) with sensing and communication capabilities (1). The mobility of data collection sinks moving to the network areas and gathering the information from sensors.

References

  1. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, pp. 393-422, 2002.
  2. W. Lindner and S. Madden, "Data management issues in disconnected sensor networks," in GI Jahrestagung (2), 2004, pp. 349-354.
  3. L. Song and D. Hatzinakos, "Architecture of Wireless Sensor Networks with Mobile Sinks: Sparse Deploying Case", Submitted to IEEE Trans. on Wireless Communications, Mar. 2004, revised Sep. 2004.
  4. L. Song and D. Hatzinakos, "Architecture of Wireless Sensor Networks with Mobile Sinks: Multiple Access Case", Under submission
  5. R. C. Shah, S. Roy, S. Jain, and W. Brunette, "Data MULEs: Modeling a three-tier architecture for sparse sensor networks," in Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, SNPA 2003, Anchorage, AK, May 11 2003, pp. 30-41.
  6. F. Zhao and L. Guibas, Wireless Sensor Networks: An Information Processing Approach. Elsevier/Morgan-Kaufmann, 2004.
  7. Aazhang, B., Chakrabarti, A. & Sabharwal, A. (2003). 'Using Predictable Observer Mobility for Power Ecient Design of Sensor Networks'. In Proc., 2nd Int. Workshop on Information Processing in Sensor Networks (IPSN), pp. 129145, Palo Alto, CA, USA. Also in Lecture Notes in Computer Science, Vol. (2634), pp. 129-145

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