Fair Buffer Allocation Scheme for Integrated Wireless Sensor and Vehicular Networks Using Markov Decision Processes

In sparsely deployed Wireless Sensor Networks (WSNs) the end to end connectivity between sensor nodes and the sink is not always available. To allow communication between sensor nodes and the sink, mobile vehicular nodes often come into play to collect data from isolated nodes, temporarily store it in their buffer and ultimately deliver to the sink. In these store and forward networks, buffers at the roadside relay nodes become critical resources for overall network performance and need to be allocated fairly among sensor nodes. In this paper we have proposed a fair buffer allocation policy for roadside relay nodes in an integrated wireless sensor and vehicular network scenario. We have considered a network with sparsely deployed sensors for gathering desired information from surroundings which is ultimately delivered to the sink via vehicular nodes. In particular, we first present the model of the buffer at the road side relay node and then formulate constrained semi- Markov decision process (SMDP) for fair buffer management. The SMDP provides an optimal decision policy to achieve fair buffer allocation at the roadside relay nodes. The model is flexible and can be realized using look up table approach. Performance evaluation results reveal the significance of the proposed policy in achieving the fair buffer allocation for different number of buffer states as well as data arrival rates.

[1]  Ali H. Sayed,et al.  Performance Analysis of Multiband OFDM UWB Communications With Application to Range Improvement , 2007, IEEE Transactions on Vehicular Technology.

[2]  Mooi Choo Chuah,et al.  Integrated Buffer and Route Management in a DTN with Message Ferry , 2006 .

[3]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Trans. Wirel. Commun..

[4]  Dusit Niyato,et al.  Performance Analysis of the Vehicular Delay Tolerant Network , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[5]  Thrasyvoulos Spyropoulos,et al.  Optimal Buffer Management Policies for Delay Tolerant Networks , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[6]  R. Tandra,et al.  Fundamental limits on detection in low SNR under noise uncertainty , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[7]  Liaoyuan Zeng,et al.  Spectrum efficiency optimization in multiuser Ultra Wideband cognitive radio networks , 2010, 2010 7th International Symposium on Wireless Communication Systems.

[8]  Xin Wang,et al.  Joint Sensing-Channel Selection and Power Control for Cognitive Radios , 2011, IEEE Transactions on Wireless Communications.

[9]  Cyril Leung,et al.  Resource allocation in an OFDM-based cognitive radio system , 2009, IEEE Transactions on Communications.

[10]  Joel J. P. C. Rodrigues,et al.  Wireless Sensor Networks: a Survey on Environmental Monitoring , 2011, J. Commun..

[11]  Yiyang Pei,et al.  Energy-Efficient Design of Sequential Channel Sensing in Cognitive Radio Networks: Optimal Sensing Strategy, Power Allocation, and Sensing Order , 2011, IEEE Journal on Selected Areas in Communications.

[12]  Lieguang Zeng,et al.  Adaptive Optimal Buffer Management Policies for Realistic DTN , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[13]  G.R. Aiello,et al.  Design of a multiband OFDM system for realistic UWB channel environments , 2004, IEEE Transactions on Microwave Theory and Techniques.

[14]  Dusit Niyato,et al.  Optimization of the Mobile Router and Traffic Sources in Vehicular Delay-Tolerant Network , 2009, IEEE Transactions on Vehicular Technology.

[15]  Kalle Ruttik,et al.  Distributed Sensing in Multiband Cognitive Networks , 2011, IEEE Transactions on Wireless Communications.

[16]  A. Thesen,et al.  Jointly Optimized Buffer Allocation and Sequencing Rules for a FMS , 1998 .

[17]  Farid Farahmand,et al.  Evaluating the Impact of Storage Capacity Constraints on Vehicular Delay-Tolerant Networks , 2009, 2009 Second International Conference on Communication Theory, Reliability, and Quality of Service.