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Adopting the Named Data Networking (NDN) architecture for Vehicular Ad Hoc Networks (VANETs) can help improve the communication among vehicles because of the data-centric nature of NDN. Routing in vehicular NDNs is still a challenge because of high mobility and intermittent connections. This paper proposes a new progressive segment routing approach that takes into consideration how vehicles are distributed among different roads, with the goal of choosing well-traveled roads over less-traveled roads to reduce the failure rate of packet delivery. A novel criterion for determining progress of routing is designed to guarantee that the destination will be reached even if a temporary loop may be formed in the path. Simulation results demonstrate that the proposed progressive segment routing algorithm can achieve better performance than existing algorithms for vehicular NDNs.

Network traffic balancing plays a key role in improving network performance. Recently, a new source routing technology, segment routing (SR), has been proposed to increase the network programming ability. SR expresses an end-to-end logical path as a sequence of segments, each of which represents the shortest path between its upstream node and downstream node. This new routing mechanism calls for a new traffic engineering method, i.e., Segment Routing Traffic Engineering (SRTE). In this paper, we devote ourselves to leveraging SRv6 to steer multiple flows in the network with the goal of minimizing the bandwidth utilization of the most congested link. Different from existing methods, we do not limit the number of available segments. We formulate this problem as an integer programming model. After proving the NP-hardness of this problem, we propose an efficient algorithm based on restricted widest paths. Comprehensive experimental results show that our method realizes similar routing performance as the optimal method while reducing the computation time by orders of magnitude.

Mobile Ad hoc Network (MANET) is the cornerstone for the Internet of Things (IoT) and Vehicle to Everything (V2X) networks, its devices are remarkable of lightweight to be portable and free to join or disjoined the network. Therefore, one of the MANET routing types is reactive routing protocols. Reactive routing protocols set up the connection between devices either on-demand such as Ad Hoc On-demand Distance Vector (AODV) protocol or source routing such as Dynamic Source Routing (DSR) protocol. Reactive routing protocols increase routing overhead on discovering new routes. Thus routing overhead, and delay will increase. In this paper, the method of generating a fuzzy model is presented. Also, a tuned fuzzy stability model is introduced to handle the imprecision of routing decisions by the Fuzzy Stability model for Ad Hoc On-demand Distance Vector (FSAODV) and Fuzzy Stability model for Dynamic Source Routing (FSDSR). The results showed that FSAODV and FSDSR have outperformed the state of art protocols AODV and DSR respectively.

The traditional business models exploited in networking are changing into industry verticals, which in turn builds new applications with striking and specific requirements. Therefore, the service-oriented, fully programmable, and flexible features that translate to sliced-capable networks are fundamentals in the design, deployment, and orchestration of networks such as 5G and beyond. Also, application consumption experiences are moving towards pervasiveness, and it is necessary to address the established inter-domain constraints uniformly. Leveraged by SDN, Cloud/Edge Computing, and NFV, several state-of-the-art proposals aim to address multi-domain slice deployment. However, they focus on multi-domain control plane efforts, leaving numerous data plane challenges openly. This paper seeks to overcome the multi-domain slice establishing issues through a source routing and BGP-based approach to provide slice abstraction to cope with application requirements. A proof-of-concept called NASOR was implemented and validated using VxFs use-cases. The results showcase its deployment suitability in traditional core networks and enhancement of the end-user experience.

Vehicular Ad-hoc NETwork (VANET) is a subcategory of Mobile Ad-hoc NETwork (MANET) which is one of the popular emerging research areas. On one side increase in the number of vehicles, and on the other side due to the presence of communication unit i.e. On Board Unit (OBU) in vehicles helped in the creation of a new network called as VANET. VANET is becoming so popular that it is widely used for different applications that may be safety or non-safety applications. An effective routing protocol is required for the efficient use of VANET for different applications which can optimize different generic parameters of VANET like end-to-end delay, number of hops, etc. Altough multiple paths exist between a source and a destination but the routing protocols evaluate a single path for the transmission of information packets based on parameters like shortest distance towards the destination, density of vehicles, number of hops, etc. Different swarm intelligence techniques like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), etc. can be used in VANET to optimize the parameters used in the routing protocol. In this chapter, Ant Colony Optimization (ACO) is used to establish multiple routes between nodes which is vital in the network where network connectivity is random and is frequently changing. This also helps in the parallel transmission of packets in multi-path which reduces end-to-end delay. For this proposed work, a variation of end-to-end delay with respect to transmission distance and a number of vehicles is compared with the existing VANET routing protocol i.e. Geographic Source Routing (GSR), Anchor based Street Traffic Aware Routing (A-STAR). The comparison shows that the proposed work performs better as compared to GSR and A-STAR. To implement multi-path routes MongoDB—an open source distributed database is used and the corresponding operation on the database is implemented using node-red. Selection of effective route and intermediate hop for the transmission of emergency information is essential. The optimized route in VANET not only saves the overall transmission time but also reduces the end-to-end delay. For the optimization of route and number of hops in VANET, another swarm intelligence technique i.e. Particle Swarm Intelligence (PSO) can be used through which the transmission of emergency information with optimum delay is proposed.

The aim of this work is the development of Source Routing Minimum Cost Forwarding (SRMCF) protocol over IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH), evaluating the performance of these protocols for the Internet of Things (IoT), and different healthcare, medical monitoring, and urban mobility applications. To perform this evaluation, this work is making use of the OpenWSN project platform, which implements IEEE 802.15.4e in an open-source environment. The evaluation process is also being done in the most recent version of the OpenMote-B platform. Another goal of this research is to give contribution to the investigation of the applicability of quality of service (QoS) applied to the IEEE 802.15.4e standard. In the present stage of development, the efforts are concentrated on the programming of the required code and the adaptation of the OpenWSN stack. Experimental results have shown that the proposed protocol is capable of reducing Packet Loss Ratio (PLR) and energy consumption in comparison to the Routing Protocol for Low Power and Lossy Networks (RPL). In the next steps the team will also investigate the possibilities to explore long-range routing techniques using the OpenMote platforms, together with xBee, LoraWAN, Raspberry PI, and Arduino platforms.

A novel node misbehavior detection system called GIFTED is proposed for a multihop wireless ad hoc network (WAHN) whose nodes may selfishly refuse to forward transit packets. The system guesses the nodes’ intrinsic forwarding trustworthiness (IFT) by analyzing end-to-end path performance rather than utilizing unreliable and incentive incompatible low-layer mechanisms. It can work with occasional IFT jumps, directional antennae, multichannel transmission, end-to-end encrypted packets, any single-path source routing protocol, and any number of selfish nodes; this makes it a valuable alternative to existing misbehavior detection schemes. GIFTED relies on approximate decomposition of a path equation system arising from successive performance reports from source nodes. The ability to near-perfectly guess IFT in the presence of various perturbations is demonstrated through Monte Carlo and time-true simulations, and compared with an existing weighted path trust scheme.

Link-flooding attack (LFA) is a new type of DDoS attack used to flood and congest the crucial network links, which has severely damaged enterprise networks. LFA can be launched by large-scale low-rate legitimate data flows with quite a low cost and is difficult to detect. While target areas in a network can be easily isolated since the crucial links are unavailable. SDN architecture provides new opportunities to address this critical network security problem with its global view of traffic monitoring enabled by the separation of data plane and control plane. Recently, segment routing (SR), which is an evolution of source routing, has been viewed as a promising technique for flow rerouting and failure recovery. Segment routing is a lightweight easy-deployed scheme known for its flexibility, scalability, and applicability. Therefore, in this paper, we try to mitigate LFA with segment rerouting within the SDN architecture. With the comprehensive network-wide view of the data flows and links, we first design a monitoring mechanism to detect LFA based on the availability of the crucial links. Then we use segment routing to detour the congested flows and alleviate the burden on the crucial links. Finally. the LFA bots will be identified and the malicious traffic will be blocked. Sufficient evaluations demonstrate that our LFA defense can efficiently detect LFA and preserve the network services, while only introduce a little signaling overhead between the controllers and data plane.

When a link fails in Software Defined Networks (SDN), the flows that use the failed link need to be rerouted over other paths. To achieve this rerouting task, researchers have proposed reactive and proactive recovery approaches. In reactive approach, upon failure, SDN controller computes new paths for the affected flows and installs them on demand. In proactive approach, the SDN controller pre-calculates backup paths and installs them on the switches in advance. While proactive approach minimizes packet loss and delay, it introduces a new problem, namely excessive usage of limited TCAM memory at SDN switches. In this paper, we consider two promising techniques (namely source routing and segment routing), and propose a new proactive technique called Segmented Source Routing (SSR). SSR uses source routing but in a segmented manner: one from the failure detecting node to an emergency node and one from emergency node to the destination. After addressing various challenges in placing emergency nodes and assigning emergency nodes to flows, our simulations shows that SSR maintains the same level of performance of pure source routing while significantly reducing the memory overhead, computation overhead, and the packet sizes as it shortens the source routes and avoids storing them at every node.

One of the most dangerous threats to Wireless Sensor Networks (WSN) are wormhole attacks due to their capacity to manipulate routing and application data in real time and cause important damages to the integrity, availability, and confidentiality of network data. In this work, an empirical method to launch such attack (which is successful) on IEEE 802.15.4/Zigbee devices with source routing enabled is adopted to find signatures for detecting wormhole attacks in real environments. It uses the KillerBee framework with algorithms for packet manipulation through a malicious node to capture and inject malicious packets in victim nodes. Besides, a reverse variant of wormhole attack is presented and executed. To evidence the realization of this threat by the attacking software, the experimental framework includes XBee S2C nodes. The results include recommendations, detection signatures and future work to face wormhole attacks involving source routing protocols like DSR.

The nodes in wireless sensor networks (WSN) are typically resource constrained so that they can maintain only a few routes. More-capable nodes can insert extra routing information, i.e. source routing header (SRH), into packets to instruct the resource constrained ones to route the packet. A WSN with deeper depth requires longer SRH, thus leaving less space of a packet for the user data. We analyze the relationship between the length of the user data and the maximum depth of a WSN based on RPL and IEEE 802.15.4. The results can guide the application designers and the network administrators in selecting a suitable length of user data to guarantee that the data can be routed to each sensor nodes. Simulation results prove the correctness of our analysis.

Today, more concerns are raised to Software Defined Networks (SDN) paradigm since it is a promising concept that offers programmability and scalability by decoupling control and data planes. However, many problems have arisen due to the huge amount of control messages exchanged periodically between the controller and Forwarding Elements (FE) and the limited space of Ternary Content-Addressable Memory TCAM into the switches. The standard Hop-by-Hop forwarding scheme requires that the controller installs at least one flow entry for each flow on each switch. This may lead to a significant bandwidth overhead and unbalanced flow tables. Unfortunately, this scheme seems to be no longer suitable for application neither in SD-LAN nor in SD-WAN.

The migration of network functions (NFs) to datacenters, as promoted by Network Function Virtualization (NFV), raises the need for service chaining (i.e., steering traffic through a sequence of NFs). Service chaining is typically performed by installing forwarding entries in switches within datacenters (DCs). However, as the number of service chains in DCs grows, switches will be required to maintain a large amount of forwarding state. This will raise a dataplane scalability issue, due to the relatively small flow table size of switches. To mitigate this problem, we present a software-defined network (SDN) based source routing architecture for scalable service chaining, at which the NF-path is encoded into the packet header obviating the need for any forwarding state and lookup in the switches. We assess the feasibility and efficiency of our architecture using a prototype implementation.

A mobile ad hoc network (MANET) is a group of autonomous mobile nodes that wirelessly communicate with each other to form a wireless dynamic topology network. It works without requiring any centralized pre-existing administration units (infrastructure less network). There are many studies that focus on improving source-destination route stability and lifetime by modifying the existing MANET routing protocols. In this paper, a fuzzy-based approach is proposed to enhance the ad hoc on-demand distance vector (AODV) reactive routing protocol’s performance by selecting the most trusted nodes to construct the route between the source and destination nodes. In this scheme, the nodes’ parameters, such as residual energy, node mobility, and number of hop counts, are fed through a fuzzy inference system to compute the value of the node trust level, which can be used as a metric to construct an optimal path from source to destination. The results of the simulation show that the proposed approach performs better than the traditional AODV routing protocol and minimum battery cost routing protocol in terms of average control overhead, packet delivery ratio, network throughput, and average end-to-end delay. The file in this item is the publisher version (published version) of the article.

This paper addresses the path selection problem arising in multi-hop sensor networks, e.g., Smart Grids. A set of multi-hop paths, of varying transmission quality, connect source and destination nodes. The source must select one path for each message to send without knowing the state of the hops. It can however use information deduced from earlier transmissions to decide on a good path for the current message. The goal is to maximize the discounted number of successfully delivered messages. We prove that the myopic routing policy, arguably the most appealing known way to tackle this problem, can permanently ignore good paths. We also generalize an empirically proven good approach, the Whittle index, and show its intractability for the problem at hand. We propose a new tractable metric, Harmonic Discounted Index (HDI), as a measure of attractiveness of transmitting over a path. We evaluate the performance of our HDI metric in a variety of simulation scenarios revealing a superior performance compared to all alternative index policies.

As the IPv6 Internet grows, alias resolution in IPv6 becomes more important. Traditional IPv4 alias resolution techniques such as Ally do not work for IPv6 because of protocol differences. Recent techniques adopted specifically for IPv6 have shown promise, but utilize source routing, which has since been deprecated, or rely upon sequential fragment identifiers supported on only a third of router interfaces. As a result, IPv6 alias resolution remains an open problem.

Wireless sensor-actuator networks (WSANs) offer an appealing communication technology for process automation applications. However, such networks pose unique challenges due to their critical demands on reliability and real-time performance. While industrial WSANs have received attention in the research community, most published results to date focused on the theoretical aspects and were evaluated based on simulations. There is a critical need for experimental research on this important class of WSANs. We developed an experimental testbed by implementing several key network protocols of WirelessHART, an open standard for WSANs widely adopted in the process industries, including multi-channel TDMA with shared slots at the MAC layer and reliable graph routing supporting path redundancy. We then performed a comparative study of the two alternative routing approaches adopted by WirelessHART, namely source routing and graph routing. Our study shows that graph routing leads to significant improvement over source routing in term of worst-case reliability, at the cost of longer latency and higher energy consumption. It is therefore important to employ graph routing algorithms specifically designed to optimize latency and energy efficiency.

Wireless revolutionizes local area communications permitting the general public to provide communications services as well as to become micro-providers in User-centric Networks (UCNs).

We propose three mechanisms to manage nodes energy and improve the efficiency of real-time routing protocols in sensor networks. To preserve nodes' resources and to improve network fluidity, the first mechanism removes each useless packet due to its insufficient deadline in reaching the sink. To reinforce the packet real-time aspect, the second mechanism selects from the current-node queue the most urgent packet to be forwarded first. For a better node energy balancing, the third mechanism uses both the residual energy and the relay speed of the forwarding candidate neighbour to select the next forwarder of the current packet. These mechanisms are simple to implement, require very little states and rely only on local primitives. In addition they can be easily integrated in any geographic routing protocol. Associated with the real-time routing protocol SPEED in TinyOS and evaluated in the simulator TOSSIM, our proposals achieved good performance in terms of node energy balancing, packet loss ratio and energy consumption.