Future Internet Routing Design for Massive Failures and Attacks

Given the high complexity and increasing traffic load of the Internet, geo-correlated challenges caused by large-scale disasters or malicious attacks pose a significant threat to dependable network communications. To understand its characteristics, we propose a critical-region identification mechanism and incorporate its result into a new graph resilience metric, compensated Total Geographical Graph Diversity. Our metric is capable of characterizing and differentiating resiliency levels for different physical topologies. We further analyze the mechanisms attackers could exploit to maximize the damage and demonstrate the effectiveness of a network restoration plan. Based on the geodiversity in topologies, we present the path geodiverse problem and two heuristics to solve it more efficiently compared to the optimal algorithm. We propose the flow geodiverse problem and two optimization formulations to study the tradeoff among cost, end-to-end delay, and path skew with multipath forwarding. We further integrate the solution to above models into our cross-layer resilient protocol stack, ResTP–GeoDivRP. Our protocol stack is prototyped and implemented in the network simulator ns-3 and emulated in our KanREN testbed. By providing multiple GeoPaths, our protocol stack provides better path restoration performance than Multipath TCP

A cross layer multi hop network architecture for wireless Ad Hoc networks

In this paper, a novel decentralized cross-layer multi-hop cooperative network architecture is presented. Our architecture involves the design of a simple yet efficient cooperative flooding scheme,two decentralized opportunistic cooperative forwarding mechanisms as well as the design of Routing Enabled Cooperative Medium Access Control (RECOMAC) protocol that spans and incorporates the physical, medium access control (MAC) and routing layers for improving the performance of multihop communication. The proposed architecture exploits randomized coding at the physical layer to realize cooperative diversity. Randomized coding alleviates relay selection and actuation mechanisms,and therefore reduces the coordination among the relays. The coded packets are forwarded via opportunistically formed cooperative sets within a region, without communication among the relays and without establishing a prior route. In our architecture, routing layer functionality is submerged into the MAC layer to provide seamless cooperative communication while the messaging overhead to set up routes, select and actuate relays is minimized. RECOMAC is shown to provide dramatic performance improvements, such as eight times higher throughput and ten times lower end-to-end delay as well as reduced overhead, as compared to networks based on well-known IEEE 802.11 and Ad hoc On Demand Distance Vector (AODV) protocols

RECOMAC: a cross-layer cooperative network protocol for wireless ad hoc networks

A novel decentralized cross-layer multi-hop cooperative protocol, namely, Routing Enabled Cooperative Medium Access Control (RECOMAC) is proposed for wireless ad hoc networks. The protocol architecture makes use of cooperative forwarding methods, in which coded packets are forwarded via opportunistically formed cooperative sets within a region, as RECOMAC spans the physical, medium access control (MAC) and routing layers. Randomized coding is exploited at the physical layer to realize cooperative transmissions, and cooperative forwarding is implemented for routing functionality, which is submerged into the MAC layer, while the overhead for MAC and route set up is minimized. RECOMAC is shown to provide dramatic performance improvements of eight times higher throughput and one tenth of end-to-end delay than that of the conventional architecture in practical wireless mesh networks

Identifying Design Requirements for Wireless Routing Link Metrics

In this paper, we identify and analyze the requirements to design a new routing link metric for wireless multihop networks. Considering these requirements, when a link metric is proposed, then both the design and implementation of the link metric with a routing protocol become easy. Secondly, the underlying network issues can easily be tackled. Thirdly, an appreciable performance of the network is guaranteed. Along with the existing implementation of three link metrics Expected Transmission Count (ETX), Minimum Delay (MD), and Minimum Loss (ML), we implement inverse ETX; invETX with Optimized Link State Routing (OLSR) using NS-2.34. The simulation results show that how the computational burden of a metric degrades the performance of the respective protocol and how a metric has to trade-off between different performance parameters

Effectiveness of Reconfigurable Intelligent Surfaces to Enhance Connectivity in UAV Networks

Reconfigurable intelligent surfaces (RISs) are expected to make future 6G networks more connected and resilient against node failures, due to their ability to introduce controllable phase-shifts onto impinging electromagnetic waves and impose link redundancy. Meanwhile, unmanned aerial vehicles (UAVs) are prone to failure due to limited energy, random failures, or targeted failures, which causes network disintegration that results in information delivery loss. In this paper, we show that the integration between UAVs and RISs for improving network connectivity is crucial. We utilize RISs to provide path diversity and alternative connectivity options for information flow from user equipments (UEs) to less critical UAVs by adding more links to the network, thereby making the network more resilient and connected. To that end, we first define the criticality of UAV nodes, which reflects the importance of some nodes over other nodes. We then employ the algebraic connectivity metric, which is adjusted by the reflected links of the RISs and their criticality weights, to formulate the problem of maximizing the network connectivity. Such problem is a computationally expensive combinatorial optimization. To tackle this problem, we propose a relaxation method such that the discrete scheduling constraint of the problem is relaxed and becomes continuous. Leveraging this, we propose two efficient solutions, namely semi-definite programming (SDP) optimization and perturbation heuristic, which both solve the problem in polynomial time. For the perturbation heuristic, we derive the lower and upper bounds of the algebraic connectivity obtained by adding new links to the network. Finally, we corroborate the effectiveness of the proposed solutions through extensive simulation experiments.Comment: 14 pages, 8 figures, journal paper. arXiv admin note: text overlap with arXiv:2308.0467

Efficient Wireless Security Through Jamming, Coding and Routing

There is a rich recent literature on how to assist secure communication between a single transmitter and receiver at the physical layer of wireless networks through techniques such as cooperative jamming. In this paper, we consider how these single-hop physical layer security techniques can be extended to multi-hop wireless networks and show how to augment physical layer security techniques with higher layer network mechanisms such as coding and routing. Specifically, we consider the secure minimum energy routing problem, in which the objective is to compute a minimum energy path between two network nodes subject to constraints on the end-to-end communication secrecy and goodput over the path. This problem is formulated as a constrained optimization of transmission power and link selection, which is proved to be NP-hard. Nevertheless, we show that efficient algorithms exist to compute both exact and approximate solutions for the problem. In particular, we develop an exact solution of pseudo-polynomial complexity, as well as an epsilon-optimal approximation of polynomial complexity. Simulation results are also provided to show the utility of our algorithms and quantify their energy savings compared to a combination of (standard) security-agnostic minimum energy routing and physical layer security. In the simulated scenarios, we observe that, by jointly optimizing link selection at the network layer and cooperative jamming at the physical layer, our algorithms reduce the network energy consumption by half