Cooperation Enforcement for Packet Forwarding Optimization in Multi-hop Ad-hoc Networks

Ad-hoc networks are independent of any infrastructure. The nodes are autonomous and make their own decisions. They also have limited energy resources. Thus, a node tends to behave selfishly when it is asked to forward the packets of other nodes. Indeed, it would rather choose to reject a forwarding request in order to save its energy. To overcome this problem, the nodes need to be motivated to cooperate. To this end, we propose a self-learning repeated game framework to enforce cooperation between the nodes of a network. This framework is inspired by the concept of "The Weakest Link" TV game. Each node has a utility function whose value depends on its cooperation in forwarding packets on a route as well as the cooperation of all the nodes that form this same route. The more these nodes cooperate the higher is their utility value. This would establish a cooperative spirit within the nodes of the networks. All the nodes will then more or less equally participate to the forwarding tasks which would then eventually guarantee a more efficient packets forwarding from sources to respective destinations. Simulations are run and the results show that the proposed framework efficiently enforces nodes to cooperate and outperforms two other self-learning repeated game frameworks which we are interested in.Comment: Published in the proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2012), Paris, France, 201

A Joint Model for IEEE 802.15.4 Physical and Medium Access Control Layers

Many studies have tried to evaluate wireless networks and especially the IEEE 802.15.4 standard. Hence, several papers have aimed to describe the functionalities of the physical (PHY) and medium access control (MAC) layers. They have highlighted some characteristics with experimental results and/or have attempted to reproduce them using theoretical models. In this paper, we use the first way to better understand IEEE 802.15.4 standard. Indeed, we provide a comprehensive model, able more faithfully to mimic the functionalities of this standard at the PHY and MAC layers. We propose a combination of two relevant models for the two layers. The PHY layer behavior is reproduced by a mathematical framework, which is based on radio and channel models, in order to quantify link reliability. On the other hand, the MAC layer is mimed by an enhanced Markov chain. The results show the pertinence of our approach compared to the model based on a Markov chain for IEEE 802.15.4 MAC layer. This contribution allows us fully and more precisely to estimate the network performance with different network sizes, as well as different metrics such as node reliability and delay. Our contribution enables us to catch possible failures at both layers.Comment: Published in the proceeding of the 7th International Wireless Communications and Mobile Computing Conference (IWCMC), Istanbul, Turkey, 201

Tracking Topology Dynamicity for Link Prediction in Intermittently Connected Wireless Networks

Through several studies, it has been highlighted that mobility patterns in mobile networks are driven by human behaviors. This effect has been particularly observed in intermittently connected networks like DTN (Delay Tolerant Networks). Given that common social intentions generate similar human behavior, it is relevant to exploit this knowledge in the network protocols design, e.g. to identify the closeness degree between two nodes. In this paper, we propose a temporal link prediction technique for DTN which quantifies the behavior similarity between each pair of nodes and makes use of it to predict future links. We attest that the tensor-based technique is effective for temporal link prediction applied to the intermittently connected networks. The validity of this method is proved when the prediction is made in a distributed way (i.e. with local information) and its performance is compared to well-known link prediction metrics proposed in the literature.Comment: Published in the proceedings of the 8th International Wireless Communications and Mobile Computing Conference (IWCMC), Limassol, Cyprus, 201

Tensor-Based Link Prediction in Intermittently Connected Wireless Networks

Through several studies, it has been highlighted that mobility patterns in mobile networks are driven by human behaviors. This effect has been particularly observed in intermittently connected networks like DTN (Delay Tolerant Networks). Given that common social intentions generate similar human behavior, it is relevant to exploit this knowledge in the network protocols design, e.g. to identify the closeness degree between two nodes. In this paper, we propose a temporal link prediction technique for DTN which quantifies the behavior similarity between each pair of nodes and makes use of it to predict future links. Our prediction method keeps track of the spatio-temporal aspects of nodes behaviors organized as a third-order tensor that aims to records the evolution of the network topology. After collapsing the tensor information, we compute the degree of similarity for each pair of nodes using the Katz measure. This metric gives us an indication on the link occurrence between two nodes relying on their closeness. We show the efficiency of this method by applying it on three mobility traces: two real traces and one synthetic trace. Through several simulations, we demonstrate the effectiveness of the technique regarding another approach based on a similarity metric used in DTN. The validity of this method is proven when the computation of score is made in a distributed way (i.e. with local information). We attest that the tensor-based technique is effective for temporal link prediction applied to the intermittently connected networks. Furthermore, we think that this technique can go beyond the realm of DTN and we believe this can be further applied on every case of figure in which there is a need to derive the underlying social structure of a network of mobile users.Comment: 13 pages, 9 figures, 8 tables, submitted to the International Journal of Computer and Telecommunications Networking (COMNET

Extended Finite State Machine based test generation for an OpenFlow switch

Implementations of an OpenFlow (OF) switch, a crucial Software Defined Networking (SDN) component, are prone to errors caused by developer mistakes or/and ambiguous requirements stated in the OF documents. The paper is devoted to test derivation for related OF switch implementations. A model based test generation strategy is proposed. It relies on an Extended Finite State Machine (EFSM) specification that describes the functional behaviour of the switch-to-controller communication while potential faults/misconfigurations are expressed via corresponding mutation operators. We propose a method for deriving a test suite that contains distinguishing sequences for the specification EFSM and corresponding mutants. The proposed approach is implemented as a testbed to automatically derive and execute the test suites against different versions of an OF implementation. Preliminary experimental evaluation has shown the effectiveness of the proposed approach. Further on, the derived test suites have been able to detect a number of functional inconsistencies such as erroneous responses to the Flow Mod adding rules with specific 'action' values in an available Open vSwitch implementatio