Abderrahmen Mtibaa

Cooperative load balancing scheme for edge computing resources

Edge Computing, as a solution to leveraging computation capabilities at the edge of the network, is emerging. One key challenge for edge computing is offering its computing service with a low service blocking and low latency that otherwise translate to an inefficient deployment of a Edge computing system. Unlike cloud computing, the computing resources in edge computing are limited. One way to deal with this limitation is by enabling cooperation between data centers.

DICE: Dynamic Multi-RAT Selection in the ICN-enabled Wireless Edge

Coupled with the rapid increase in mobile device users and the bandwidth and latency demands are the continuous increase of devices processing capabilities, storage, and wireless connectivity options. The multiple radio access technology (multi-RAT) is proposed to satisfy mobile users increasing needs. The Information-Centric Networking (ICN) paradigm is better tuned (than the current Internet Protocol approach) to support multi-RAT communications. ICN eschews the connection-based content retrieval model used today and has desirable features such as data naming, in-network caching, and device mobility--a paradigm ripe for exploration. We propose DICE, an ICN forwarding strategy that helps a device dynamically select a subset of its multi-RAT interfaces for communication. DICE assesses the state of edge links and network congestion to determine the minimum number of interfaces required to to perform data delivery. We perform simulations to compare DICEs performance with bestroute2 and multicast strategies (part of the named data networking simulator, ndnSIM). We show that DICE is the best of both worlds: providing a higher delivery ratio (0.2-2 times) and much lower overhead (by 2-8 times) for different packet rates.

Message in a Bottle: Extending Communication Coverage Via Boat-to-Boat WiFi Communication

Maritime tasks have been costly and challenging due to the geographical, spatial, and dynamic nature of the area of operations. With the high deployment cost and unreliability of Wireless Sensor Networks (WSN), Autonomous Surface Vehicles (ASV) have been recently deployed to perform various maritime tasks. In this paper, we propose communication methods to reduce maritime task data retrieval. We define an optimization problem that leverages Device-2-Device (D2D) WiFi communication to retrieve data beyond the radio range of the central data-collection entity. We empirically analyze WiFi performance on-water given single-hop and multi-hop D2D communication. We quantitatively compare two data retrieval methods: em end-to-end ad-hoc and em hop-by-hop opportunistic. Our results highlight that while the inexpensive hop-by-hop opportunistic helps cover larger areas, end-to-end ad-hoc performs up-to 60× faster delivery.

STAR: STAble routing for hidden interfering primary user problems in mobile cognitive radio networks

In mobile Cognitive Radio Networks (CRNs), the frequent link breakage and wireless interference urged the need for novel stable routing solutions. In this paper, we propose STAR, a stable routing protocol that aims at selecting interference-free and durable paths. We investigate the particular Hidden interfering Primary User (HIPU) problem caused by the un-detectable presence of the primary user in the transmission range of the secondary users resulting on severe packet loss. While existing CRNs routing solution, generally, overlook the interference caused by the Hidden Interfering Primary User (HIPU), STAR defines a HIPU-free transmission zone, that enables successful transmission and selects a stable route that is free from interference along the path to the destination. STAR uses prediction based model to estimate the link stability and the link propagation delay. To quantitatively select the best stable links along the route, STAR implements an objective function, cognitive stable link (CSL), that captures node mobility, interference by the HIPU, link propagation delay, and the distance towards the destination. We evaluate STAR, while comparing its throughput, latency, and packet loss ratio to three other protocols, namely PCTC, J-SRCA and AODV. Evaluation on MATLAB shows that STAR achieves higher throughput while reducing the end-to-end latency and the packet loss in the network.

Request aggregation: the good, the bad, and the ugly

Request aggregation is a fundamental feature of named data networking (NDN). This feature aims to improve consumers quality of experience and reduce network traffic by reducing content retrieval latency and eliminating redundant communication, respectively. However, the negative aspects of request aggregation have not been studied. In this paper, we inspect different facets of request aggregation and introduce one of its harmful behavior, which can create an implicit Denial of Service (iDoS) vulnerability.

A Case for Information Centric Networking For Smart Grid Communications

The smart grid, with its large array of networked devices and bidirectional data flow between the end-users and the grid, presents new requirements in service reliability, communication latency, and data delivery. The traditional TCP/IP communication paradigm was not designed to handle these requirements at the envisioned scale. This calls for a novel networking paradigm. This paper makes the case for the use of the Information Centric Networking (ICN) paradigm to create the smart grid network architecture. We quantitatively assess the gains resulting from ICNs inherent functionalities, such as concurrent use of multiple interfaces, request aggregation, and stateful forwarding, which enable timely critical message delivery and fast packet re-transmissions. We perform simulations to compare IP and ICN-based smart grid deployments. Our results show that the ICN-based solution outperforms the IP-based solution, especially in a network with packet losses.