Distributed Joint Cluster Formation and Resource Allocation Scheme for Cooperative Data Collection in Virtual MIMO-Based M2M Networks

An efficient data collection scheme plays an important role for the real-time intelligent monitoring in many machine-to-machine (M2M) networks. In this paper, a distributed joint cluster formation and resource allocation scheme for data collection in cluster-based M2M networks is proposed. Specifically, in order to utilize the advantages of cooperation, we first propose a hierarchical transmission model which contains two communication phases. In the first phase, the intracluster information sharing is carried out by all the nodes within the same cluster. Then these nodes transmit the total information to the BS cooperatively with virtual-MIMO (VMIMO) protocol in the second phase. To grasp the properties and advantages of this cooperative transmission strategy, the theoretical analysis results are provided. The key issue in this system is to form the clusters and allocate resources efficiently. Since the optimization problem on this issue is an NP-hard problem, a feasible joint scheme for the cluster formation and resource allocation is proposed in this paper, which is carried out via coalition formation game with a distributed algorithm. This scheme can reduce the complexity while keeping an attractive performance. Simulation results show the properties of the proposed scheme and its advantages when comparing with the noncooperative scheme for the data collection in a practical scenario.

[1]  Xiaoyan Feng,et al.  A new optimal transmit and receive diversity scheme , 2001, 2001 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (IEEE Cat. No.01CH37233).

[2]  Zhong Fan,et al.  Emerging technologies and research challenges for 5G wireless networks , 2014, IEEE Wireless Communications.

[3]  Zhu Han,et al.  Efficient and reliable multiple access for advanced metering in future smart grid , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[4]  Sherali Zeadally,et al.  Machine-to-Machine (M2M) Communications in Vehicular Networks , 2012 .

[5]  Xiao Lu,et al.  Machine-to-machine communications for home energy management system in smart grid , 2011, IEEE Communications Magazine.

[6]  Vangalur S. Alagar,et al.  Publishing and discovering context-dependent services , 2013, Human-centric Computing and Information Sciences.

[7]  D. K. Lobiyal,et al.  Performance evaluation of data aggregation for cluster-based wireless sensor network , 2013, Human-centric Computing and Information Sciences.

[8]  Hsuan-Jung Su,et al.  Joint optimization of cluster formation and power control for interference-limited machine-to-machine communications , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[9]  Xin Wang,et al.  An energy-efficient virtual MIMO transmission scheme for cluster-based wireless sensor networks , 2010, 2010 IEEE 12th International Conference on Communication Technology.

[10]  Hung-Yun Hsieh,et al.  Data-centric clustering for data gathering in machine-to-machine wireless networks , 2013, 2013 IEEE International Conference on Communications Workshops (ICC).

[11]  Deshi Li,et al.  The optimized method of cluster-head deployment based on GA-WCA in Wireless Sensor Networks , 2010, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).

[12]  David I. Laurenson,et al.  A resource allocation algorithm for cluster-based cooperative MIMO in Wireless Sensor Networks , 2009, SoftCOM 2009 - 17th International Conference on Software, Telecommunications & Computer Networks.

[13]  Zhu Han,et al.  Physical layer security: Coalitional games for distributed cooperation , 2009, 2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.

[14]  Ameer Ahmed Abbasi,et al.  A survey on clustering algorithms for wireless sensor networks , 2007, Comput. Commun..

[15]  Mohsen Guizani,et al.  Distributed rate and admission control in home M2M networks: A non-cooperative game approach , 2011, 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[16]  Zhong Fan,et al.  M2M communications for e-health: Standards, enabling technologies, and research challenges , 2012, 2012 6th International Symposium on Medical Information and Communication Technology (ISMICT).

[17]  Makoto Takizawa,et al.  A Survey on Clustering Algorithms for Wireless Sensor Networks , 2010, 2010 13th International Conference on Network-Based Information Systems.

[18]  Dusit Niyato,et al.  Cooperative transmission for meter data collection in smart grid , 2012, IEEE Communications Magazine.

[19]  Ma Chaw Mon Thein,et al.  An Energy Efficient Cluster-Head Selection for Wireless Sensor Networks , 2010, 2010 International Conference on Intelligent Systems, Modelling and Simulation.

[20]  Yueming Cai,et al.  A Cooperative Communication Scheme Based on Coalition Formation Game in Clustered Wireless Sensor Networks , 2012, IEEE Transactions on Wireless Communications.