Ant-based evidence distribution with periodic broadcast in attacked wireless network

In order to establish trust among nodes in large wireless networks, the trust certicates need to be distributed and be readily accessible. However, even so, searching for trust certicates will still become highly cost and delay especially when wireless network is suering CTS jamming attack. We believe the individual solution can lead us to solve this combination problems in the future. Therefore, in this work, we investigate the delay and cost of searching a distributed certicate and the adverse eects of fabiricated control packet attacks on channel throughput and delivery ratio respectively, and propose two techniques that can improve the eciency of searching for such certicates in the network and mitigate the CTS jamming attack's eect. Evidence Distribution based on Periodic Broadcast (EDPB) is the rst solution we presented to help node to quickly locate trust certicates in a large wireless sensor network. In this solution, we not only take advantages from swarm intelligence alogrithm, but also allow nodes that carrying certicates to periodically announce their existence. Such announcements, together with a swarm-intelligence pheromone pdate procedure, will leave traces on the nodes to lead query packets toward the certicate nodes. We then investigate the salient features of this schema and evaluate its performance in both static and mobile networks. This schema can also be used for other essential information dissemination in mobile ad hoc networks. The second technqiue, address inspection schema (AIS) xes vulnerabilities exist in distribution coordinating function (DCF) dened in IEEE 802.11 standard so that each node has the ability to beat the impact of CTS jamming attack and furthermore, benets network throughput. We then perform ns-2 simulations to evaluate the benet of AIS

Optimizing the Replication of Multi-Quality Web Applications Using ACO and WoLF

This thesis presents the adaptation of Ant Colony Optimization to a new NP-hard problem involving the replication of multi-quality database-driven web applications (DAs) by a large application service provider (ASP). The ASP must assign DA replicas to its network of heterogeneous servers so that user demand is satisfied and replica update loads are minimized. The algorithm proposed, AntDA, for solving this problem is novel in several respects: ants traverse a bipartite graph in both directions as they construct solutions, pheromone is used for traversing from one side of the bipartite graph to the other and back again, heuristic edge values change as ants construct solutions, and ants may sometimes produce infeasible solutions. Experiments show that AntDA outperforms several other solution methods, but there was room for improvement in the convergence rates of the ants. Therefore, in an attempt to achieve the goals of faster convergence and better solution values for larger problems, AntDA was combined with the variable-step policy hill-climbing algorithm called Win or Learn Fast (WoLF). In experimentation, the addition of this learning algorithm in AntDA provided for faster convergence while outperforming other solution methods

Information distribution and recharging dispatch strategy in large wireless networks

Large wireless networks are envisioned to play increasingly important roles as more and more mobile wireless devices and Internet of Things (IoT) devices are put in use. In these networks, it is often the case that some critical information needs to be readily accessible, requiring a careful design of the information distribution technique. In this work, we at first propose PeB, Periodic Broadcast, that takes advantage of periodic broadcast from the information server(s) to leave traces for nodes requesting for the information while maintaining a low overhead. Similar to swarm intelligence, PeB requires each node to keep track of traces, or past records of information flow, through itself toward information servers. We present our extensive investigation of the PeB scheme on cost and network dynamics as compared to other state-of-the-art techniques. When the devices run out of battery, they become static and need to be recharged by the wireless charging vehicles (WCVs). Often times, WCV receives a number of charging requests and form a Hamiltonian cycle and visit these nodes one-by-one. We also propose a heuristic algorithm, termed Quad, that generates a Hamiltonian cycle in a square plane. We then focus on the theoretical study of the length of the Hamiltonian cycles in such networks

A Computational Field Framework for Collaborative Task Execution in Volunteer Clouds

The increasing diffusion of cloud technologies is opening new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing their computational resources. The high dynamism and unpredictability of such scenarios call for decentralized self-* approaches to guarantee QoS. We present a simulation framework for collaborative task execution in volunteer clouds and propose one concrete instance based on Ant Colony Optimization, which is validated through a set of simulation experiments based on Google workload data

Power consumption optimization and delay based on ant colony algorithm in network-on-chip

With a further increase of the number of on-chip devices, the bus structure has not met the requirements. In order to make better communication between each part, the chip designers need to explore a new NoC structure to solve the interconnection of an on-chip device. For the purpose of improving the performance of a network-on-chip without a significant increase in power consumption, the paper proposes a network-on-chip that selects NoC (Network-On-Chip) platform with 2-dimension mesh as the carrier and incorporates communication power consumption and delay into a unified cost function. The paper uses ant colony optimization for the realization of NoC map facing power consumption and delay potential. The experiment indicates that in comparison with a random map, single objective optimization can separately account for (30%~47%) and (20%~39%) of communication power consumption and execution time, and joint objective optimization can further excavate the potential of time dimension in a mapping scheme dominated by the power

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

Multi-Dimensional Resource Orchestration in Vehicular Edge Networks

In the era of autonomous vehicles, the advanced technologies of connected vehicle lead to the development of driving-related applications to meet the stringent safety requirements and the infotainment applications to improve passenger experience. Newly developed vehicular applications require high-volume data transmission, accurate sensing data collection, and reliable interaction, imposing substantial constrains on vehicular networks that solely rely on cellular networks to fetch data from the Internet and on-board processors to make driving decisions. To enhance multifarious vehicular applications, Heterogeneous Vehicular Networks (HVNets) have been proposed, in which edge nodes, including base stations and roadside units, can provide network connections, resulting in significantly reduced vehicular communication cost. In addition, caching servers are equipped at the edge nodes, to further alleviate the communication load for backhaul links and reduce data downloading delay. Hence, we aim to orchestrate the multi-dimensional resources, including communication, caching, and sensing resources, in the complex and dynamic vehicular environment to enhance vehicular edge network performance. The main technical issues are: 1) to accommodate the delivery services for both location-based and popular contents, the scheme of caching contents at edge servers should be devised, considering the cooperation of caching servers at different edge nodes, the mobility of vehicles, and the differential requirements of content downloading services; 2) to support the safety message exchange and collective perception services for vehicles, communication and sensing resources are jointly allocated, the decisions of which are coupled due to the resource sharing among different services and neighboring vehicles; and 3) for interaction-intensive service provisioning, e.g., trajectory design, the forwarding resources in core networks are allocated to achieve delay-sensitive packet transmissions between vehicles and management controllers, ensuring the high-quality interactivity. In this thesis, we design the multi-dimensional resource orchestration schemes in the edge assisted HVNets to address the three technical issues. Firstly, we design a cooperative edge caching scheme to support various vehicular content downloading services, which allows vehicles to fetch one content from multiple caching servers cooperatively. In particular, we consider two types of vehicular content requests, i.e., location-based and popular contents, with different delay requirements. Both types of contents are encoded according to fountain code and cooperatively cached at multiple servers. The proposed scheme can be optimized by finding an optimal cooperative content placement that determines the placing locations and proportions for all contents. To this end, we analyze the upper bound proportion of content caching at a single server and provide the respective theoretical analysis of transmission delay and service cost (including content caching and transmission cost) for both types of contents. We then formulate an optimization problem of cooperative content placement to minimize the overall transmission delay and service cost. As the problem is a multi-objective multi-dimensional multi-choice knapsack one, which is proved to be NP-hard, we devise an ant colony optimization-based scheme to solve the problem and achieve a near-optimal solution. Simulation results are provided to validate the performance of the proposed scheme, including its convergence and optimality of caching, while guaranteeing low transmission delay and service cost. Secondly, to support the vehicular safety message transmissions, we propose a two-level adaptive resource allocation (TARA) framework. In particular, three types of safety message are considered in urban vehicular networks, i.e., the event-triggered message for urgent condition warning, the periodic message for vehicular status notification, and the message for environmental perception. Roadside units are deployed for network management, and thus messages can be transmitted through either vehicle-to-infrastructure or vehicle-to-vehicle connections. To satisfy the requirements of different message transmissions, the proposed TARA framework consists of a group-level resource reservation module and a vehicle-level resource allocation module. Particularly, the resource reservation module is designed to allocate resources to support different types of message transmission for each vehicle group at the first level, and the group is formed by a set of neighboring vehicles. To learn the implicit relation between the resource demand and message transmission requests, a supervised learning model is devised in the resource reservation module, where to obtain the training data we further propose a sequential resource allocation (SRA) scheme. Based on historical network information, the SRA scheme offline optimizes the allocation of sensing resources (i.e., choosing vehicles to provide perception data) and communication resources. With the resource reservation result for each group, the vehicle-level resource allocation module is then devised to distribute specific resources for each vehicle to satisfy the differential requirements in real time. Extensive simulation results are provided to demonstrate the effectiveness of the proposed TARA framework in terms of the high successful reception ratio and low latency for message transmissions, and the high quality of collective environmental perception. Thirdly, we investigate forwarding resource sharing scheme to support interaction intensive services in HVNets, especially for the delay-sensitive packet transmission between vehicles and management controllers. A learning-based proactive resource sharing scheme is proposed for core communication networks, where the available forwarding resources at a switch are proactively allocated to the traffic flows in order to maximize the efficiency of resource utilization with delay satisfaction. The resource sharing scheme consists of two joint modules: estimation of resource demands and allocation of available resources. For service provisioning, resource demand of each traffic flow is estimated based on the predicted packet arrival rate. Considering the distinct features of each traffic flow, a linear regression scheme is developed for resource demand estimation, utilizing the mapping relation between traffic flow status and required resources, upon which a network switch makes decision on allocating available resources for delay satisfaction and efficient resource utilization. To learn the implicit relation between the allocated resources and delay, a multi-armed bandit learning-based resource sharing scheme is proposed, which enables fast resource sharing adjustment to traffic arrival dynamics. The proposed scheme is proved to be asymptotically approaching the optimal strategy, with polynomial time complexity. Extensive simulation results are presented to demonstrate the effectiveness of the proposed resource sharing scheme in terms of delay satisfaction, traffic adaptiveness, and resource sharing gain. In summary, we have investigated the cooperative caching placement for content downloading services, joint communication and sensing resource allocation for safety message transmissions, and forwarding resource sharing scheme in core networks for interaction intensive services. The schemes developed in the thesis should provide practical and efficient solutions to manage the multi-dimensional resources in vehicular networks