Modelling and Delay Analysis of Intermittently Connected Roadside Communication Networks

During the past decade, consumers all over the world have been showing an incremental interest in vehicular technology. The world’s leading vehicle manufacturers have been and are still engaged in continuous competitions to present for today’s sophisticated drivers, vehicles that gratify their demands. This has lead to an outstanding advancement and development of the vehicular manufacturing industry and has primarily contributed to the augmentation of the twenty first century’s vehicle with an appealing and intelligent personality. Particularly, the marriage of information technology to the transport infrastructure gave birth to a novel communication paradigm known as Vehicular Networking. More precisely, being equipped with computerized modules and wireless communication devices, the majority of today’s vehicles qualify to act as typical mobile network nodes that are able to communicate with each other. In addition, these vehicles can as well communicate with other wireless units such as routers, access points, base stations and data posts that are arbitrarily deployed at fixed locations along roadways. These fixed units are referred to as Stationary Roadside Units (SRUs). As a result, ephemeral and self-organized networks can be formed. Such networks are known as Vehicular Networks and constitute the core of the latitudinarian Intelligent Transportation System (ITS) that embraces a wide variety of applications including but not limited to: traffic management, passenger and road safety, environment monitoring and road surveillance, hot-spot guidance, on the fly Internet access, remote region connectivity, information sharing and dissemination, peer-to-peer services and so forth. This thesis presents an in-depth investigation on the possibility of exploiting mobile vehicles to establish connectivity between isolated SRUs. A network of intercommunicating SRUs is referred to as an Intermittently Connected Roadside Communication Network (ICRCN). While inter-vehicular communication as well as vehicle-to-SRU communication has been widely studied in the open literature, the inter-SRU communication has received very little attention. In this thesis, not only do we focus on inter-SRU connectivity establishment through the transport infrastructure but also on the objective of achieving delay-minimal data delivery from a source SRU to a destination SRU in. This delivery process is highly dependent on the vehicular traffic behaviour and more precisely on the arrival times of vehicles to the source SRU as well as these vehicles’ speeds. Vehicle arrival times and speeds are, in turn, highly random and are not available a priori. Under such conditions, the realization of the delay-minimal data delivery objective becomes remarkably challenging. This is especially true since, upon the arrival of vehicles, the source SRU acts on the spur of the moment and evaluates the suitability of the arriving vehicles. Data bundles are only released to those vehicles that contribute the most to the minimization of the average bundle end-to-end delivery delays. Throughout this thesis, several schemes are developed for this purpose. These schemes differ in their enclosed vehicle selection criterion as well as the adopted bundle release mechanism. Queueing models are developed for the purpose of capturing and describing the source SRU’s behaviour as well as the contents of its buffer and the experienced average bundle queueing delay under each of theses schemes. In addition, several mathematical frameworks are established for the purpose of evaluating the average bundle transit delay. Extensive simulations are conducted to validate the developed models and mathematical analyses

Delay-Aware Flow Scheduling in Low Latency Enterprise Datacenter Networks: Modeling and Performance Analysis

Real-time interactive application workloads (e.g., Web search, social networking, and so on) appear in the form of a large number of mini requests and responses flowing over the datacenters' networks. They end up being sewed all together to constitute a user-requested task or computation (e.g., display a complete Facebook timeline). Applications as such strictly impose low latency flow completion, since the service's quality is decreed by quick aggregation of responses to the largest possible fraction of requests and their delivery back to the user. This paper presents a deadline-aware flow scheduling (DAFS). In addition to reducing the average flow completion time (FCT), DAFS aims at decreasing the deadline mismatch and blocking probabilities, hence improving the average application throughput. An analytical queuing model is formulated herein to capture the datacenter's network dynamics and evaluate its performance when operating under DAFS. The model is validated through extensive simulations whose results also show that DAFS outperforms existing multi-queue-based priority mechanisms by 52% in terms of the average FCT and a range of 7%-29% in terms of the average throughput.This paper was made possible by Grant NPRP 5-137-2-045 from the Qatar National Research Fund (a member of Qatar Foundation).Scopu

Reliability-aware service provisioning in NFV-enabled enterprise datacenter networks

Network Function Visualization (NFV) enables the complete decoupling of Network Functions (NFs) (e.g., firewall, intrusion detection, routing, etc.) from physical middleboxes used to implement service-specific and strictly ordered chains of these NFs. Precisely, NFV allows for dispatching NFs as plain software instances called Virtual Network Functions (VNFs) running on virtual machines hosted by one or more industry standard physical machines. This, however, introduces vulnerabilities (e.g., hard-/soft-ware failures, etc) causing the break down of the entire VNF chain. The functionality of NFV-enabled networks impose higher reliability requirements than traditional networks. This paper encloses an in-depth investigation of a reliability-aware joint VNF placement and flow routing optimization problem. This problem is formulated as a complex Integer Linear Program (ILP). A heuristic is proposed in order to overcome this ILP's complexity. Thorough numerical analysis are conducted to verify and assert the correctness and effectiveness of the proposed heuristic.This work was made possible by the NPRP 5-137-2-045 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authorsScopu

Prioritizing deadline-constrained data flows in cloud datacenter networks

Real-time interactive application workloads (e.g. web search, social networking, etc.) are composed of a remarkably large number of mini request partitions that require stringent delayminimal aggregation of responses and their delivery back to the user. This paper presents a novel Time-Deadline-AwarepFabric (TDA-pFabric) being a data transport design whose objectives are two-fold: i) reducing the mean Flow Completion Time (FCT), the deadline mismatch and blocking probabilities as well as ii) improving the mean application throughput. A stochastic queueing model is proposed herein to capture TDA-pFabric's dynamics and evaluate its performance. The model is validated through extensive simulations whose results also show that TDA-pFabric exhibits significant improvements over existing designs in terms of the above-listed quality-of-service metrics.Scopu

A Reliability-Aware Network Service Chain Provisioning with Delay Guarantees in NFV-Enabled Enterprise Datacenter Networks

Traditionally, service-specific network functions (NFs) (e.g., Firewall, intrusion detection system, etc.) are executed by installation-and maintenance-costly hardware middleboxes that are deployed within a datacenter network following a strictly ordered chain. NF virtualization (NFV) virtualizes these NFs and transforms them into instances of plain software referred to as virtual NFs (VNFs) and executed by virtual machines, which, in turn, are hosted over one or multiple industry-standard physical machines. The failure (e.g., hardware or software) of any one of a service chain's VNFs leads to breaking down the entire chain and causing significant data losses, delays, and resource wastage. This paper establishes a reliability-aware and delay-constrained (READ) routing optimization framework for NFV-enabled datacenter networks. READ encloses the formulation of a complex mixed integer linear program (MILP) whose resolution yields an optimal network service VNF placement and traffic routing policy that jointly maximizes the achieved respective reliabilities of supported network services and minimizes these services' respective end-to-end delays. A heuristic algorithm dubbed Greedy-k-shortest paths (GSP) is proposed for the purpose of overcoming the MILP's complexity and develop an efficient routing scheme whose results are comparable to those of READ's optimal counterparts. Thorough numerical analyses are conducted to evaluate the network's performance under GSP, and hence, gauge its merit; particularly, when compared to existing schemes, GSP exhibits an improvement of 18.5% in terms of the average end-to-end delay as well as 7.4% to 14.8% in terms of reliability. 1 2004-2012 IEEE.Scopu