Formal probabilistic performance verification of randomly-scheduled wireless sensor networks

Energy efficiency in Wireless Sensor Networks (WSN) is one of the most critical issue regardless of the target application. While scheduling sensors by partitions to preserve energy is a simple and intuitive approach in this context, it is also important to not compromise on the main performance requirements of the considered application. For mission-critical WSN applications, different Quality of Service (QoS) requirements on network performance have to be met. Besides, various assumptions, may effectively impact the sensing performance capabilities of the network. Nevertheless, most analysis techniques focus on the average performance values, and do not consider neither the targeted QoS requirements, nor the probabilistic feature of the algorithm. Based on the theorem proving approach, we first provide, in this paper, an accurate formal analysis of the network lifetime maximization problem, under QoS constraints, for randomlyscheduled wireless sensor networks. After that, we tackle the higher-order-logic formalization of the intrusion coverage intensity, for a modified version of the randomized scheduling, with more realistic assumptions for the intrusion object, in a two or three dimensional plane.

[1]  Yang Xiao,et al.  WSN10-3: Maximizing Network Lifetime under QoS Constraints in Wireless Sensor Networks , 2006, IEEE Globecom 2006.

[2]  Osman Hasan,et al.  Formalized Probability Theory and Applications Using Theorem Proving , 2015 .

[3]  Peter Csaba Ölveczky,et al.  Formal Analysis of Leader Election in MANETs Using Real-Time Maude , 2015, Software, Services, and Systems.

[4]  Yang Xiao,et al.  IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, PAPER ID: TPDS-0307-0605.R1 1 Random Coverage with Guaranteed Connectivity: Joint Scheduling for Wireless Sensor Networks , 2022 .

[5]  Ian F. Akyildiz,et al.  BorderSense: Border patrol through advanced wireless sensor networks , 2011, Ad Hoc Networks.

[6]  Tarek Mhamdi,et al.  Information-Theoretic Analysis using Theorem Proving , 2012 .

[7]  L.F.W. van Hoesel,et al.  Modelling and Verification of the LMAC Protocol for Wireless Sensor Networks , 2007, IFM.

[8]  Mingyan Liu,et al.  Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[9]  Xiaojiang Du,et al.  Three Dimensional Intrusion Objects Detection under Randomized Scheduling Algorithm in Sensor Networks , 2008, 2008 The 4th International Conference on Mobile Ad-hoc and Sensor Networks.

[10]  Paolo Ballarini,et al.  Model Checking Medium Access Control for Sensor Networks , 2006, Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (isola 2006).

[11]  Pramod K. Varshney,et al.  QoS Support in Wireless Sensor Networks: A Survey , 2004, International Conference on Wireless Networks.

[12]  Di Tian,et al.  A coverage-preserving node scheduling scheme for large wireless sensor networks , 2002, WSNA '02.

[13]  Xiaojiang Du,et al.  Intrusion Objects with Shapes under Randomized Scheduling Algorithm in Sensor Networks , 2008, 2008 The 28th International Conference on Distributed Computing Systems Workshops.

[14]  Sofiène Tahar,et al.  Towards the Formal Performance Analysis of Wireless Sensor Networks , 2013, 2013 Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises.

[15]  Yang Xiao,et al.  A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks , 2006, Mob. Networks Appl..

[16]  Ju Wang,et al.  E-HIPA: An Energy-Efficient Framework for High-Precision Multi-Target-Adaptive Device-Free Localization , 2017, IEEE Transactions on Mobile Computing.

[17]  Aarti Gupta,et al.  Formal hardware verification methods: A survey , 1992, Formal Methods Syst. Des..

[18]  Kin K Leung,et al.  Randomized scheduling algorithm for data aggregation in wireless sensor networks , 2010, 2010 European Wireless Conference (EW).

[19]  Xiaojiang Du,et al.  Two and three-dimensional intrusion object detection under randomized scheduling algorithms in sensor networks , 2009, Comput. Networks.

[20]  Osman Hasan,et al.  Formal probabilistic analysis using theorem proving , 2008 .

[21]  Christel Baier,et al.  Principles of model checking , 2008 .

[22]  Emmanouil Fanourgakis Modelling and Verication of QoS properties of a Biomedical Wireless Sensor Network , 2012 .

[23]  Vinayak S. Naik,et al.  A line in the sand: a wireless sensor network for target detection, classification, and tracking , 2004, Comput. Networks.

[24]  Wang Yi,et al.  Model-based validation of QoS properties of biomedical sensor networks , 2008, EMSOFT '08.

[25]  Peter Csaba Ölveczky,et al.  A Framework for Mobile Ad hoc Networks in Real-Time Maude , 2014, WRLA.

[26]  Feng Xia,et al.  QoS Challenges and Opportunities in Wireless Sensor/Actuator Networks , 2008, Sensors.

[27]  Sofiène Tahar,et al.  Formal Probabilistic Analysis of a WSN-Based Monitoring Framework for IoT Applications , 2016, FTSCS.

[28]  Sofiène Tahar,et al.  Formalization of Entropy Measures in HOL , 2011, ITP.

[29]  Kamel Barkaoui,et al.  Probabilistic verification and evaluation of Backoff procedure of the WSN ECo-MAC protocol , 2010, ArXiv.

[30]  Cinzia Bernardeschi,et al.  Analysis of Wireless Sensor Network Protocols in Dynamic Scenarios , 2009, SSS.

[31]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[32]  Quazi Mamun,et al.  A Coverage-Based Scheduling Algorithm for WSNs , 2014, Int. J. Wirel. Inf. Networks.

[33]  Sofiène Tahar,et al.  Formal Analysis of a Scheduling Algorithm for Wireless Sensor Networks , 2011, ICFEM.

[34]  Kui Wu,et al.  Randomized Coverage-Preserving Scheduling Schemes for Wireless Sensor Networks , 2005, NETWORKING.

[35]  Xiaojiang Du,et al.  Weaving a proper net to catch large objects in wireless sensor networks , 2010, IEEE Transactions on Wireless Communications.

[36]  Peter Csaba Ölveczky,et al.  Formal Modeling and Analysis of the OGDC Wireless Sensor Network Algorithm in Real-Time Maude , 2007, FMOODS.

[37]  Sofiène Tahar,et al.  Formal Probabilistic Analysis of a Wireless Sensor Network for Forest Fire Detection , 2012, SCSS.

[38]  Sofiène Tahar,et al.  Formal Probabilistic Analysis of Lifetime for a WSN-based Monitoring Application , 2016, VECoS.

[39]  Jan J. M. M. Rutten,et al.  Mathematical techniques for analyzing concurrent and probabilistic systems , 2004, CRM monograph series.

[40]  Matthias Fruth,et al.  Probabilistic Model Checking of Contention Resolution in the IEEE 802.15.4 Low-Rate Wireless Personal Area Network Protocol , 2006, Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (isola 2006).

[41]  Hridesh Rajan,et al.  Slede: a domain-specific verification framework for sensor network security protocol implementations , 2008, WiSec '08.

[42]  Sofiène Tahar,et al.  Formal probabilistic analysis of detection properties in wireless sensor networks , 2014, Formal Aspects of Computing.

[43]  Frits W. Vaandrager,et al.  Analysis of a clock synchronization protocol for wireless sensor networks , 2009, Theor. Comput. Sci..

[44]  Ying Zhang,et al.  Coverage and Detection of a Randomized Scheduling Algorithm in Wireless Sensor Networks , 2010, IEEE Transactions on Computers.

[45]  Yang Xiao,et al.  Lightweight Deployment-Aware Scheduling for Wireless Sensor Networks , 2005, Mob. Networks Appl..

[46]  Reformatting Fighter Tactics , .

[47]  Jun Sun,et al.  Towards a Model Checker for NesC and Wireless Sensor Networks , 2011, ICFEM.

[48]  Sofiène Tahar,et al.  Formalization of Normal Random Variables in HOL , 2016, CICM.

[49]  Xianbin Wang,et al.  Applications of Wireless Sensor Networks in Marine Environment Monitoring: A Survey , 2014, Sensors.

[50]  M. Gordon,et al.  Introduction to HOL: a theorem proving environment for higher order logic , 1993 .