Abdelmajid Khelil

An epidemic model for information diffusion in MANETs

Choosing appropriate information dissemination strategies is crucial in mobile ad hoc networks (MANET) due to the frequent topology changes. Flooding-based approaches like diffusion have a strong similarity with epidemic spreading of diseases. Applying epidemiological models to information diffusion allows the evaluation of such strategies depending on the MANET characteristics, e.g. the node density. In order to choose appropriate strategies at run time, the model should be easily evaluated.In this paper, an epidemic model is developed for a simple information diffusion algorithm based on simulation results. We analytically investigate the impact of node density on information diffusion. The analytical model allows the evaluation at runtime, even on devices with restricted resources, and thus enables mobile nodes to dynamically adapt their diffusion strategies depending on the local node density.

Hypergossiping: A generalized broadcast strategy for mobile ad hoc networks

Broadcasting is a commonly used communication primitive needed by many applications and protocols in mobile ad hoc networks (MANET). Unfortunately, most broadcast solutions are tailored to one class of MANETs with respect to node density and node mobility and are unlikely to operate well in other classes. In this paper, we introduce hypergossiping, a novel adaptive broadcast algorithm that combines two strategies. Hypergossiping uses adaptive gossiping to efficiently distribute messages within single network partitions and implements an efficient heuristic to distribute them across partitions. Simulation results in ns-2 show that hypergossiping operates well for a broad range of MANETs with respect to node densities, mobility levels and network loads.

Contact-based mobility metrics for delay-tolerant ad hoc networking

Mobility plays a major role in mobile ad hoc networks (MANETs) since it stresses networking tasks such as routing on one hand but aids to increase the network capacity and to overcome network partitioning on the other hand. To benefit from node mobility, a new class of MANET protocols and applications are designed to be delay-tolerant and mobility-aided. For delay-tolerant mobility-aided networking mobility on a large time-scale is a key feature. So far, in MANETs, the mobility is investigated on a short time-scale. That is why we present novel mobility metrics that quantify large time-scale mobility. Our approach is based on the pair-wise contacts between mobile nodes. We present a detailed statistical study of our novel metrics using the widely used random waypoint mobility model as an example. For the random waypoint model we introduce an analytical model, which allows protocol developers to analytically compute some of the designed metrics. In order to provide an easy access to these metrics in a network simulator, we provide a framework for ns-2.

TRCCIT: Tunable reliability with Congestion Control for Information Transport in Wireless Sensor Networks

A core functionality of Wireless Sensor Networks (WSNs) is to transport information from the network to the application/user. The evolvable application reliability requirements and the fluctuating perturbations lead to continuous deviation between the attained and desired reliability. Using an existing approach that guarantees a highest reliability is not appropriate for WSN as this over-provisioning wastes the most valuable resources, e.g., energy. In this paper, we present a new approach called as Tunable Reliability with Congestion Control for Information Transport (TRCCIT) in WSN. To provide probabilistically guaranteed tunable reliability TRCCIT implements localized techniques such as probabilistic adaptive retransmissions, hybrid acknowledgment and retransmission timer management. TRCCIT pro-actively alleviates the network congestion by opportunistically transporting the information on multiple paths. TRCCIT fulfills application reliability requirements in a localized way, which is desirable for scalability and adaptability to large scale WSNs. Simulation results show that TRCCIT provides tunable reliability and efficiently mitigates the congestion.

On Modeling the Reliability of Data Transport in Wireless Sensor Networks

Data transport is a core function for wireless sensor networks (WSNs) with different applications having varied requirements on the reliability and timeliness of data delivery. While node redundancy, inherent in WSNs, increases the fault tolerance, no guarantees on reliability levels can be assured. Furthermore, the frequent failures within WSNs impact the observed reliability over time and make it more challenging to achieve the desired reliability. Unfortunately, a framework for modeling reliability of data transport protocols in WSNs is currently missing. The existence of such a framework would simplify evaluation, comparison and also adaptation of these protocols. We formulate the problem of data transport in a WSN as a set of operations carried out on raw data. The operations aim at filtering the raw data to streamline its reliable transport towards the sink. Based on this formulation we systematically define a reliability framework. This paper argues for the usefulness of the reliability framework by classifying existing transport protocols and comparing their reliability

Enabling IoT Ecosystems through Platform Interoperability

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.

On the suitability of Device-to-Device communications for road traffic safety

In this paper, we explore recent Device-to-Device (D2D) research efforts and review their suitability to safety-critical Internet of Vehicles (IoV) applications, such as cooperative or autonomous driving. Typical to the IoV environment is the high node mobility along with strict Quality of Service (QoS) requirements, especially in terms of delay and reliability. In addition, IoV applications require geomessaging capabilities with high degree of accuracy in particular in proximity awareness. Accordingly, we qualitatively assess the effectiveness of D2D approaches to cope with high mobility and precise geomessaging. Our review work shows that current approaches ignore high relative node mobility and accurate proximity measurements, and the crucial research challenges mainly are those related to maintaining the required QoS level in highly fluctuating D2D communications. This work is meant to be a roadmap towards adopting the emerging D2D technique for critical IoV communications.

Generic Information Transport for Wireless Sensor Networks

A primary functionality of wireless sensor networks (WSNs) is transporting the information acquired by the sensors as per the desired application requirements. The diverse applications supported by WSNs also stipulate a diverse range of reliability requirements for the transport of various information types. The continuous variation of application requirements and dynamic operational perturbations complicates the design of a generic solution for information transport in WSNs. In this paper, we present a new framework for generic information transport (GIT), which considers varied application requirements and evolvable network conditions in WSNs. GIT manages the information and utilizes a probabilistic approach to ensure tunable reliability of information transport. The GIT framework is distributed in nature and performs its operations locally. The simulation results validate the tunability of the GIT framework. In some setups GIT achieves up to 4-5 times reduction in number of transmissions compared to existing approaches.

An adaptive and composite spatio-temporal data compression approach for wireless sensor networks

Wireless Sensor Networks (WSN) are often deployed to sample the desired environmental attributes and deliver the acquired samples to the sink for processing, analysis or simulations as per the application needs. Many applications stipulate high granularity and data accuracy that results in high data volumes. Sensor nodes are battery powered and sending the requested large amount of data rapidly depletes their energy. Fortunately, the environmental attributes (e.g., temperature, pressure) often exhibit spatial and temporal correlations. Moreover, a large class of applications such as scientific measurement and forensics tolerate high latencies for sensor data collection. Accordingly, we develop a fully distributed adaptive technique for spatial and temporal in-network data compression with accuracy guarantees. We exploit the spatio-temporal correlation of sensor readings while benefiting from possible data delivery latency tolerance to further minimize the amount of data to be transported to the sink. Using real data, we demonstrate that our proposed scheme can provide significant communication/energy savings without sacrificing the accuracy of collected data. In our simulations, we achieved data compression of up to 95% on the raw data requiring around 5% of the original data to be transported to the sink.

Increasing the resilience of critical SCADA systems using peer-to-peer overlays

Supervisory Control and Data Acquisition (SCADA) systems are migrating from isolated to highly-interconnected large scale architectures. In addition, these systems are increasingly composed of standard Internet technologies and use public networks. Hence, while the SCADA functionality has increased, its vulnerability to cyber threats has also risen. These threats often lead to reduced system availability or compromised data integrity, eventually resulting in risks to public safety. Therefore, enhancing the reliability and security of system operation is an urgent need. Peer-to-Peer (P2P) techniques allow the design of self-organizing Internet-scale communication overlay networks. Two inherent resilience mechanisms of P2P networks are path redundancy and data replication. This paper shows how SCADA systems resilience can be improved by using P2P technologies. In particular, the two previously mentioned resilience mechanisms allow circumventing crashed nodes and detecting manipulated control data.