TY - GEN
T1 - Multi-hop scheduling and local data link aggregation dependant Qos in modeling and simulation of power-aware wireless sensor networks
AU - Iyer, Vasanth
AU - Iyengar, S. S.
AU - Murthy, Rama
AU - Hochet, Bertrand
AU - Phoha, Vir
AU - Srinivas, M. B.
PY - 2009
Y1 - 2009
N2 - In this study of wireless sensor networks (WSN) protocols, the application Qos, system, and protocol performance metrics are measured for a large scalable wireless deployment using a typical wireless radio and an energy model. As there are many different types of WSN algorithms, we have categorized it into pro-active, re-active, and query driven information processing. A typical Qos is based on the useful lifetime of sensor nodes, after which reliability of the sensor data cannot be guaranteed and typically, a threshold such as a percentage of the sensor drains out of energy or a minimum through-put of real-time data from the sensor network is expected, which is used to compare the Qos of the routing algorithm. The results from lifetime based Qos, measured in simulation seconds, for the implemented protocols show that with varying sampled data sources for a BE Qos multi-hop deployment and varying percentage of cluster heads in a time synchronized deployment, the lifetime is based on network size and protocol invariant. However, low sensing ranges result in dense networks, and therefore, it becomes necessary to achieve an efficient medium-access protocol subjected to power constraints. Scalability of sensor network applications are based on energy energy-harvesting techniques in which the various layers of the network interoperate and extend the system network lifetime, the battery residual power per node, and the application reliability in terms of cross-layer energy savings. In this study, we have extended the lifetime metrics from a constant metrics into a break down of how much percentage of time is spent for Tx, Rx, and Idle tasks, respectively. This helps one to highlight the cross-layer energy dissipation per node and how the performance of an algorithm differs in terms of duty-cycling.
AB - In this study of wireless sensor networks (WSN) protocols, the application Qos, system, and protocol performance metrics are measured for a large scalable wireless deployment using a typical wireless radio and an energy model. As there are many different types of WSN algorithms, we have categorized it into pro-active, re-active, and query driven information processing. A typical Qos is based on the useful lifetime of sensor nodes, after which reliability of the sensor data cannot be guaranteed and typically, a threshold such as a percentage of the sensor drains out of energy or a minimum through-put of real-time data from the sensor network is expected, which is used to compare the Qos of the routing algorithm. The results from lifetime based Qos, measured in simulation seconds, for the implemented protocols show that with varying sampled data sources for a BE Qos multi-hop deployment and varying percentage of cluster heads in a time synchronized deployment, the lifetime is based on network size and protocol invariant. However, low sensing ranges result in dense networks, and therefore, it becomes necessary to achieve an efficient medium-access protocol subjected to power constraints. Scalability of sensor network applications are based on energy energy-harvesting techniques in which the various layers of the network interoperate and extend the system network lifetime, the battery residual power per node, and the application reliability in terms of cross-layer energy savings. In this study, we have extended the lifetime metrics from a constant metrics into a break down of how much percentage of time is spent for Tx, Rx, and Idle tasks, respectively. This helps one to highlight the cross-layer energy dissipation per node and how the performance of an algorithm differs in terms of duty-cycling.
KW - Algorithm complexity
KW - Distributed algorithms
KW - MAC layer duty-cycling
KW - Power aware routing
KW - Qos for link quality
KW - Renewable energy resources
KW - Wireless sensor network
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U2 - 10.1145/1582379.1582562
DO - 10.1145/1582379.1582562
M3 - Conference contribution
AN - SCOPUS:70450230554
SN - 9781605585697
T3 - Proceedings of the 2009 ACM International Wireless Communications and Mobile Computing, Connecting the World Wirelessly, IWCMC 2009
SP - 844
EP - 848
BT - Proceedings of the 2009 ACM International Wireless Communications and Mobile Computing Conference, IWCMC 2009
PB - Association for Computing Machinery (ACM)
T2 - 2009 ACM International Wireless Communications and Mobile Computing Conference, IWCMC 2009
Y2 - 21 June 2009 through 24 June 2009
ER -