Modelling and Verification of the LMAC Protocol for Wireless Sensor Networks

Fehnker, Ansgar; Hoesel, Lodewijk van; Mader, Angelika

doi:10.1007/978-3-540-73210-5_14

Cited by 74 publications

(67 citation statements)

References 7 publications

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“…Camara et al [18] applied formal methods using SPIN to verify the design bugs in protocols for MANET networks such as LAR, DREAM and OLSR. Fehnker et al [19] and Henderson et al [20] used UPPAAL to identify flaws in the WSN protocols. However, we see only a little evidence of the adoption of such approaches when ad-hoc serial communication protocols are in question.…”

Section: Related Workmentioning

confidence: 99%

Verification of an Ad-hoc Serial Communication Protocol through Model-checking: A Case Study with Echo Sounder

Majeed¹,

Saghar²,

Hameed³

et al. 2017

JSW

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Serial data transmission accounts for a considerable share of the overall communication involved in real-time embedded systems. Although there are some standard serial protocols, many systems still use ad-hoc serial protocols for communication between a control computer and a serial peripheral device. Such protocols may have flaws in them which cannot be revealed by computer simulations or testing only. To complement testing, formal methods are now widely used and have proved effective in the verification of various communication protocols. However, for serial communication specifically, most of the previous research is focused on applying formal methods for the verification of standard serial interfaces. In the current work instead, we use formal methods to verify an ad-hoc serial communication protocol between a control computer and an echo sounder. Through our case study, we show how we integrated formal modeling and model-checking methods in an existing system and as a result, we were able to discover a fault in the protocol design, which could have gone unnoticed without formal software verification.

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Section: Related Workmentioning

confidence: 99%

Verification of an Ad-hoc Serial Communication Protocol through Model-checking: A Case Study with Echo Sounder

Majeed¹,

Saghar²,

Hameed³

et al. 2017

JSW

View full text Add to dashboard Cite

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“…In [7], [14], formal verification of the LMAC protocol is investigated in the timed automaton model checker UPPAAL [1]. The LMAC network is modelled by parallel composition of single node behaviours.…”

Section: Related Workmentioning

confidence: 99%

“…The component-based approach to model the concurrency in the stabilization process was applied in [7] and [17], where the behaviour of a single node is modelled as a basic component. Indeed, the system properties are represented in terms of parallel composition of individual nodes.…”

Section: A Probabilistic Model Of the Lmac Protocolmentioning

confidence: 99%

“…In [7], the case with 5 nodes considering all the 61 topologies has been investigated. These different topologies can lead to dramatically varied verification results.…”

Section: A Probabilistic Model Of the Lmac Protocolmentioning

confidence: 99%

“…In previous works [7], [14], [17], the concurrent behaviour of the LMAC nodes was modelled using parallel decomposition. The complexity of the models rose drastically with the number of network nodes, limiting the analysis to small-sized networks far from reality.…”

Section: Introductionmentioning

confidence: 99%

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A Probabilistic Model of the LMAC Protocol for Concurrent Wireless Sensor Networks

Esparza

Zeng

Nielsen

2011

2011 Eleventh International Conference on Application of Concurrency to System Design

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Abstract-We present a probabilistic model for the network setup phase of the Lightweight Medium Access Protocol (LMAC) for concurrent Wireless Sensor Networks. In the network setup phase, time slots are allocated to the individual sensors through resolution of successive collisions. The setup phase involving collisions should preferably be as short as possible for efficiency and energy consumption reasons. This concurrent stochastic process has inherent internal nondeterminism, and we model it using combinatorics. The setup phase is modeled by a discrete time Markov chain such that we can apply results from the theory of phase type distributions. Having obtained our model we are able to find optimal protocol parameters. We have simultaneously developed a simulation model, partly to verify our analytical derivations and partly to be able to deal with systems of excessively high order or stiff systems that might cause numerical challenges. Our abstracted model has a state space of limited size where the number of states are of the order n+r+1 n , where n is number of sensors, and r is the maximum back off time. We have developed a tool, named LMAC analyzer, on the MATLAB platform to assist automatic generation and analysis of the model.

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Petri nets‐based model for the analysis of NORIA protocol

Macià

Ruiz

Mateo

et al. 2015

Concurrency and Computation

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Network rOle-based Routing Intelligent Algorithm is a novel routing algorithm for wireless sensor networks, which combine various effective techniques in order to reduce energy consumption and improve data routes. This algorithm uses role assignment for distributing tasks over the network nodes and fuzzy logic for making decisions. There is a clear need for the use of formal methods to validate the correctness of the protocols as well as performance and functionality prior to the deployment of such algorithms in a real environment. This paper presents a formal and rigorous study of Network rOle-based Routing Intelligent Algorithm. Prioritised-timed coloured petri nets (PTCPNs) have been chosen as an appropriate modelling language. In this way, PTCPNs have been used to describe complete and unambiguous specifications of system behaviour, whereas CPNTools is used to evaluate the correctness of the protocol using state space exploration and for performance evaluation using simulation. ANALYSIS OF NORIA PROTOCOL 4705 routing intelligent algorithm called Network rOle-based Routing Intelligent Algorithm (NORIA)[3] will be analysed in this paper. NORIA improves data routing in networks oriented mainly to monitoring applications, that is, those in which the information is gathered individually in each node and it is forwarded bottom-up to a special sink called here base station, which is located at the centre. Thus, the network is organised forming a tree. Furthermore, NORIA uses fuzzy logic to make routing decisions, and each node has assigned a role that will determine its functionality.Moreover, we advocate for the use of prioritised-timed coloured Petri nets (PTCPNs) [4] for several reasons. First, PTCPNs are based on rigorous mathematical definitions so that one may be capable to obtain complete and unambiguous specifications of the system behaviour. Besides, PTCPNs have a graphical notation, allowing users to track easily how the system evolves, and provide several analysis methods, including simulation, state space analysis and invariant analysis. In the literature, there are some tools for constructing and evaluating PTCPN models, but we have opted for CPNTools [5] because it is considered the de facto tool for editing, simulating and analysing PTCPNs and supports hierarchical nets, priorities and time. In addition, the toolbox provides also the necessary primitives to make your own queries (written as ML functions) to study interesting properties of the system state space. Finally, the tool monitor facilities permit us to extract relevant information from the simulations in order to evaluate system performance. Figure 3. CPN model for a node (part II).Here, the transitions Receive IPM and Receive IPM_out simulate the reception of an IPM, but the main difference between both is that the first one can be fired during that 51 units of waiting for packets and the packets information is used for the parent selection, whereas the second one (Receive IPM_out) is used to receive IPMs out of the duration of the timer. Ne...

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Modelling and Verification of the LMAC Protocol for Wireless Sensor Networks

Cited by 74 publications

References 7 publications

Verification of an Ad-hoc Serial Communication Protocol through Model-checking: A Case Study with Echo Sounder

Verification of an Ad-hoc Serial Communication Protocol through Model-checking: A Case Study with Echo Sounder

A Probabilistic Model of the LMAC Protocol for Concurrent Wireless Sensor Networks

Petri nets‐based model for the analysis of NORIA protocol

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