Resource-Management for Vehicular Real-Time Application under Hard Reliability Constraints

In this paper, we design and test a full distributed and scalable resource-management scheduler for Vehicular Real-Time applications. We dynamically allocate the access time window (at the RoadSide Units) and the access rate and traffic flows (at the Vehicular Clients) under hard reliability collision constraints. We provide the optimal memoryless scheduler for network utility maximization, showing as it presents no loss in the network average utility with respect to not real-time soft reliability schedulers. Finally, the proposed scheduler exploits an ad-hoc designed soft-input/soft-output data fusion algorithm, able to supply in real-time reliable context-information, even in the presence of fading-affected and intermittent vehicular-to-infrastructure connectivity.

[1]  H. Kushner,et al.  Analysis of adaptive step-size SA algorithms for parameter tracking , 1995, IEEE Trans. Autom. Control..

[2]  Enzo Baccarelli,et al.  Optimized Power Allocation for Multiantenna Systems Impaired by Multiple Access Interference and Imperfect Channel Estimation , 2007, IEEE Transactions on Vehicular Technology.

[3]  Enzo Baccarelli,et al.  Interference Management for Multiple Multicasts with Joint Distributed Source/Channel/Network Coding , 2013, IEEE Transactions on Communications.

[4]  Enzo Baccarelli,et al.  Optimal MIMO UWB-IR Transceiver for Nakagami-fading and Poisson-Arrivals , 2008, J. Commun..

[5]  Pramod K. Varshney,et al.  Distributed Detection and Data Fusion , 1996 .

[6]  M. S. Bazaraa,et al.  Nonlinear Programming , 1979 .

[7]  Enzo Baccarelli,et al.  Recursive Kalman-type optimal estimation and detection of hidden Markov chains , 1996, Signal Process..

[8]  Enzo Baccarelli,et al.  QoS Stochastic Traffic Engineering for the wireless support of real-time streaming applications , 2012, Comput. Networks.

[9]  Xuemin Shen,et al.  Provisioning QoS controlled media access in vehicular to infrastructure communications , 2012, Ad Hoc Networks.

[10]  Ronald W. Wolff,et al.  Stochastic Modeling and the Theory of Queues , 1989 .

[11]  Rajkumar Buyya,et al.  A survey on vehicular cloud computing , 2014, J. Netw. Comput. Appl..

[12]  Luigi V. Mancini,et al.  Scheduling Hard-Real-Time Tasks with Backup Phasing Delay , 2006, 2006 Tenth IEEE International Symposium on Distributed Simulation and Real-Time Applications.

[13]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[14]  Enzo Baccarelli,et al.  Stochastic traffic engineering for real-time applications over wireless networks , 2012, J. Netw. Comput. Appl..

[15]  Mohamed-Slim Alouini,et al.  On the Energy Detection of Unknown Signals Over Fading Channels , 2007, IEEE Transactions on Communications.

[16]  Enzo Baccarelli,et al.  Distributed and adaptive resource management in Cloud-assisted Cognitive Radio Vehicular Networks with hard reliability guarantees , 2015, Veh. Commun..

[17]  Arun Venkataramani,et al.  Energy consumption in mobile phones: a measurement study and implications for network applications , 2009, IMC '09.

[18]  Mary Ann Ingram,et al.  Six Time- and Frequency-Selective Empirical Channel Models for Vehicular Wireless LANs , 2007, 2007 IEEE 66th Vehicular Technology Conference.

[19]  Enzo Baccarelli,et al.  Optimal Self-Adaptive QoS Resource Management in Interference-Affected Multicast Wireless Networks , 2013, IEEE/ACM Transactions on Networking.

[20]  Salvatore Marano,et al.  Utility-Based Predictive Services for Adaptive Wireless Networks With Mobile Hosts , 2009, IEEE Transactions on Vehicular Technology.

[21]  Eylem Ekici,et al.  Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions , 2011, IEEE Communications Surveys & Tutorials.