EAAC: Energy-Aware Admission Control Scheme for Ad Hoc Networks
The decisions made by admission control algorithms are
based on the availability of network resources viz. bandwidth, energy,
memory buffers, etc., without degrading the Quality-of-Service (QoS)
requirement of applications that are admitted. In this paper, we
present an energy-aware admission control (EAAC) scheme which
provides admission control for flows in an ad hoc network based
on the knowledge of the present and future residual energy of the
intermediate nodes along the routing path. The aim of EAAC is to
quantify the energy that the new flow will consume so that it can
be decided whether the future residual energy of the nodes along
the routing path can satisfy the energy requirement. In other words,
this energy-aware routing admits a new flow iff any node in the
routing path does not run out of its energy during the transmission
of packets. The future residual energy of a node is predicted using
the Multi-layer Neural Network (MNN) model. Simulation results
shows that the proposed scheme increases the network lifetime. Also
the performance of the MNN model is presented.
[1] D.B. Johnson and D.A. Maltz, "Dynamic Source Routing in Ad-Hoc
Wireless Networks", Mobile Computing, Kluwer Academic Publishers,
ch. 5, pp. 153-181, 1996.
[2] C. Perkins and E. Royer, "Ad hoc On-Demand Distance Vector Routing",
Proc. 2nd IEEE Workshop on Mobile Computing Systems & Applications,
pp. 90-100, Feb. 1999.
[3] R. Asokan and A. M. Natarajan, "An approach for reducing the Endto-
end Delay and increasing the Network Lifetime in Mobile Ad hoc
Networks", Intr-l Jr. of Info. Tech., vol. 4, no. 2, pp. 121-127, 2008.
[4] Q. Sun and H. Langendoerfer, "Multicast Routing in Multimedia Communication",
Proc. 2nd Intr-l Workshop on Protocols for Multimedia Systems
(PROMS -95), pp. 452-458, 1995.
[5] C.P. Low and X. Song, "On Finding Feasible Solutions for the Delay
Constrained Group Multicast Routing Problem", IEEE Trans. on Computers,
vol. 51, pp. 581-588, 2002.
[6] V. P. Kompella, J. C. Pasquale and G.C Polyzos, "Multicast Routing in
Multimedia Communication", IEEE Trans. on Computers, vol. 51, pp.
581-588, 2002.
[7] Y. Yang and R. Kravets, "Contention-aware Admission control for Ad
Hoc Networks", IEEE Trans. on Mobile Computing, vol. 4, no. 4, 2005.
[8] K. Scott and N. Bambos, "Routing & Channel Assignment for Low Power
Transmission in PCS", Proc. IEEE Int-l Conf. on Universal Personal
Comm. (ICUPC-96), pp. 498-502, 1996.
[9] S. Singh, M. Woo and C.S. Raghavendra, "Power-aware with Routing in
Mobile Ad Hoc Networks", Proc. IV Annual ACM/IEEE Int-l Conf. on
Mobile Computing & Networking, 1998.
[10] C.-K Toh, "Maximum Battery Life Routing to Support Ubiquitous Mobile
Computing in Wireless Ad Hoc Networks", IEEE Comm. Magazine,
Jun 2001.
[11] Z. Guo and B. Malakooti, "Energy Aware Proactive MANET Routing
with Prediction on Energy Consumption" Proc. IEEE Int-l Conf. on
Wireless Algorithms, Systems and Applications, pp. 287-292, 2007.
[12] Nen-Chung W. and Yu-Li S., "A Power-Aware Multicast Routing
Protocol for Mobile Ad Hoc Networks with Mobility Prediction", Proc.
IEEE Conf. on Local Computer Networks (LCN-05), 2005.
[13] Dilip Kumar S.M. and Vijaya Kumar B.P., "Energy-Aware Multicast
Routing in MANETs based on Genetic Algorithms", Proc. XVI IEEE
Intr-l Conf. on Networks (ICON- 08), New Delhi, 2008.
[14] D. Kim, J.J. Garcia L-A, K. Obraczka, K-C Cano, and P. Manzoni,
"Routing Mechanisms for Mobile Ad Hoc Networks based on the Energy
Drain Rate", IEEE Trans. on Mobile Computing, vol 2., no. 2, 2003.
[15] K. Murugan and S. Shanmugavel, "Traffic-Dependent and Energy-Based
Time Delay Routing Algorithms for improving Energy Efficiency in
Mobile Ad Hoc Networks", EURASIP Jr. on Wireless Communications
and Networking, no. 5, pp. 625-634, 2005.
[16] Koushik K., M. Kodialam, T.V. Lakshman and L. Tassiulas, "Routing
for Network Capacity Maximization in Energy-constrained Ad-hoc Networks",
Proc. IEEE INFOCOM, 2003.
[17] Tragoudas S., and Dimitrova S., "Routing with Energy considerations
in Mobile Ad Hoc Networks", IEEE Wireless Communications and
Networking Conf. (WCNC-00), vol. 3, pp. 1258-1261, 2000.
[18] M. B. Pursley, H. B. Russell, and J. S. Wysocarski, "Energy-efficient
Transmission and Routing Protocols for Wireless Multiple-hop Networks
and Spread Spectrum Radios", Proc. EUROCOMM Conf., pp. 1-5, 2000.
[19] I-Shyan Hwang and Wen-Hsin Pang, "Energy Efficient Clustering Technique
for Multicast Routing Protocol in Wireless Ad Hoc Networks", Int-l
Jr. of Computer Science and Network Security, vol. 7, no. 8, Aug. 2007.
[20] L. Lin, N. B. Shroff, and R. Srikant, "Asymptotically Optimal Poweraware
Routing for Multihop networks with Renewable Energy Sources",
Proc. IEEE INFOCOM-05. 24th Annual Joint Conf. of IEEE Computer
and Comm. Societies, FL Mar. 2005.
[21] Zhihao Guo and B. Malakooti, "Energy Aware Proactive MANET
Routing with Prediction on Energy Consumption", Proc. Intr-l Conf. on
Wireless Algorithms, Systems and Applications, pp. 287-292, 2007.
[22] Box. G.E. and Jenkins G.M., Time Series Analysis, Holden-day, San
Francisco. 1970.
[23] G. Peter Zhang, B. Eddy Patumo and M.Y. Hu, "A Simulation Study
of Artificial Neural Networks for Nonlinear Time-Series Forecasting",
Computers and operations research, vol. 28, pp.381-396, 2001.
[24] Ruelhart, D.E. and McClelland, J. L, eds., Parallel Distributed Processing:
Explorations in the Microstructure Cognition, Cambridge, MA: The
MIT press, vol. 1, 318-362, 1986.
[25] Simon Haykin, Neural Networks: A Comprehensive Foundation,
Macmillan college publishing company, New york, 1995.
[26] , Feng Shu-hu and Guan Xiao-ji, "Energy Output Prediction Model on
Time Series Analysis and Neural Network" ÔÇöÔÇö-, 2007.
[27] Mozer N. Neural Net for Temporal Sequence Processing, Time Series
Prediction: Forecasting the future and understanding the past, Addison-
Wesley, Reading, MIT.
[28] Koskela T., Lehtokangas M., Saarinen J. and Kaski K., "Time Series
Prediction with Multilayer Perceptron, FIR and Elman neural networks",
Proc. of the World Congress on Neural Networks, INNS Press, pp. 491-
496.
[29] A. Cichocki and R. Unbehauen, Neural Networks for Optimization and
Signal Processing, John-Wiley and sons, Stuttgart, 1993.
[30] K. Fall and K. Varadhan, ns Notes and Documents, The VINT Project,
UC Berkeley, LBL, USC/ISI, and Xerox PARC, Feb. 2000.
[1] D.B. Johnson and D.A. Maltz, "Dynamic Source Routing in Ad-Hoc
Wireless Networks", Mobile Computing, Kluwer Academic Publishers,
ch. 5, pp. 153-181, 1996.
[2] C. Perkins and E. Royer, "Ad hoc On-Demand Distance Vector Routing",
Proc. 2nd IEEE Workshop on Mobile Computing Systems & Applications,
pp. 90-100, Feb. 1999.
[3] R. Asokan and A. M. Natarajan, "An approach for reducing the Endto-
end Delay and increasing the Network Lifetime in Mobile Ad hoc
Networks", Intr-l Jr. of Info. Tech., vol. 4, no. 2, pp. 121-127, 2008.
[4] Q. Sun and H. Langendoerfer, "Multicast Routing in Multimedia Communication",
Proc. 2nd Intr-l Workshop on Protocols for Multimedia Systems
(PROMS -95), pp. 452-458, 1995.
[5] C.P. Low and X. Song, "On Finding Feasible Solutions for the Delay
Constrained Group Multicast Routing Problem", IEEE Trans. on Computers,
vol. 51, pp. 581-588, 2002.
[6] V. P. Kompella, J. C. Pasquale and G.C Polyzos, "Multicast Routing in
Multimedia Communication", IEEE Trans. on Computers, vol. 51, pp.
581-588, 2002.
[7] Y. Yang and R. Kravets, "Contention-aware Admission control for Ad
Hoc Networks", IEEE Trans. on Mobile Computing, vol. 4, no. 4, 2005.
[8] K. Scott and N. Bambos, "Routing & Channel Assignment for Low Power
Transmission in PCS", Proc. IEEE Int-l Conf. on Universal Personal
Comm. (ICUPC-96), pp. 498-502, 1996.
[9] S. Singh, M. Woo and C.S. Raghavendra, "Power-aware with Routing in
Mobile Ad Hoc Networks", Proc. IV Annual ACM/IEEE Int-l Conf. on
Mobile Computing & Networking, 1998.
[10] C.-K Toh, "Maximum Battery Life Routing to Support Ubiquitous Mobile
Computing in Wireless Ad Hoc Networks", IEEE Comm. Magazine,
Jun 2001.
[11] Z. Guo and B. Malakooti, "Energy Aware Proactive MANET Routing
with Prediction on Energy Consumption" Proc. IEEE Int-l Conf. on
Wireless Algorithms, Systems and Applications, pp. 287-292, 2007.
[12] Nen-Chung W. and Yu-Li S., "A Power-Aware Multicast Routing
Protocol for Mobile Ad Hoc Networks with Mobility Prediction", Proc.
IEEE Conf. on Local Computer Networks (LCN-05), 2005.
[13] Dilip Kumar S.M. and Vijaya Kumar B.P., "Energy-Aware Multicast
Routing in MANETs based on Genetic Algorithms", Proc. XVI IEEE
Intr-l Conf. on Networks (ICON- 08), New Delhi, 2008.
[14] D. Kim, J.J. Garcia L-A, K. Obraczka, K-C Cano, and P. Manzoni,
"Routing Mechanisms for Mobile Ad Hoc Networks based on the Energy
Drain Rate", IEEE Trans. on Mobile Computing, vol 2., no. 2, 2003.
[15] K. Murugan and S. Shanmugavel, "Traffic-Dependent and Energy-Based
Time Delay Routing Algorithms for improving Energy Efficiency in
Mobile Ad Hoc Networks", EURASIP Jr. on Wireless Communications
and Networking, no. 5, pp. 625-634, 2005.
[16] Koushik K., M. Kodialam, T.V. Lakshman and L. Tassiulas, "Routing
for Network Capacity Maximization in Energy-constrained Ad-hoc Networks",
Proc. IEEE INFOCOM, 2003.
[17] Tragoudas S., and Dimitrova S., "Routing with Energy considerations
in Mobile Ad Hoc Networks", IEEE Wireless Communications and
Networking Conf. (WCNC-00), vol. 3, pp. 1258-1261, 2000.
[18] M. B. Pursley, H. B. Russell, and J. S. Wysocarski, "Energy-efficient
Transmission and Routing Protocols for Wireless Multiple-hop Networks
and Spread Spectrum Radios", Proc. EUROCOMM Conf., pp. 1-5, 2000.
[19] I-Shyan Hwang and Wen-Hsin Pang, "Energy Efficient Clustering Technique
for Multicast Routing Protocol in Wireless Ad Hoc Networks", Int-l
Jr. of Computer Science and Network Security, vol. 7, no. 8, Aug. 2007.
[20] L. Lin, N. B. Shroff, and R. Srikant, "Asymptotically Optimal Poweraware
Routing for Multihop networks with Renewable Energy Sources",
Proc. IEEE INFOCOM-05. 24th Annual Joint Conf. of IEEE Computer
and Comm. Societies, FL Mar. 2005.
[21] Zhihao Guo and B. Malakooti, "Energy Aware Proactive MANET
Routing with Prediction on Energy Consumption", Proc. Intr-l Conf. on
Wireless Algorithms, Systems and Applications, pp. 287-292, 2007.
[22] Box. G.E. and Jenkins G.M., Time Series Analysis, Holden-day, San
Francisco. 1970.
[23] G. Peter Zhang, B. Eddy Patumo and M.Y. Hu, "A Simulation Study
of Artificial Neural Networks for Nonlinear Time-Series Forecasting",
Computers and operations research, vol. 28, pp.381-396, 2001.
[24] Ruelhart, D.E. and McClelland, J. L, eds., Parallel Distributed Processing:
Explorations in the Microstructure Cognition, Cambridge, MA: The
MIT press, vol. 1, 318-362, 1986.
[25] Simon Haykin, Neural Networks: A Comprehensive Foundation,
Macmillan college publishing company, New york, 1995.
[26] , Feng Shu-hu and Guan Xiao-ji, "Energy Output Prediction Model on
Time Series Analysis and Neural Network" ÔÇöÔÇö-, 2007.
[27] Mozer N. Neural Net for Temporal Sequence Processing, Time Series
Prediction: Forecasting the future and understanding the past, Addison-
Wesley, Reading, MIT.
[28] Koskela T., Lehtokangas M., Saarinen J. and Kaski K., "Time Series
Prediction with Multilayer Perceptron, FIR and Elman neural networks",
Proc. of the World Congress on Neural Networks, INNS Press, pp. 491-
496.
[29] A. Cichocki and R. Unbehauen, Neural Networks for Optimization and
Signal Processing, John-Wiley and sons, Stuttgart, 1993.
[30] K. Fall and K. Varadhan, ns Notes and Documents, The VINT Project,
UC Berkeley, LBL, USC/ISI, and Xerox PARC, Feb. 2000.
@article{"International Journal of Information, Control and Computer Sciences:51413", author = "Dilip Kumar S.M and Vijaya Kumar B.P.", title = "EAAC: Energy-Aware Admission Control Scheme for Ad Hoc Networks", abstract = "The decisions made by admission control algorithms are
based on the availability of network resources viz. bandwidth, energy,
memory buffers, etc., without degrading the Quality-of-Service (QoS)
requirement of applications that are admitted. In this paper, we
present an energy-aware admission control (EAAC) scheme which
provides admission control for flows in an ad hoc network based
on the knowledge of the present and future residual energy of the
intermediate nodes along the routing path. The aim of EAAC is to
quantify the energy that the new flow will consume so that it can
be decided whether the future residual energy of the nodes along
the routing path can satisfy the energy requirement. In other words,
this energy-aware routing admits a new flow iff any node in the
routing path does not run out of its energy during the transmission
of packets. The future residual energy of a node is predicted using
the Multi-layer Neural Network (MNN) model. Simulation results
shows that the proposed scheme increases the network lifetime. Also
the performance of the MNN model is presented.", keywords = "Ad hoc networks, admission control, energy-aware
routing, Quality-of-Service, future residual energy, neural network.", volume = "3", number = "3", pages = "555-10", }
