Adaptive Routing Scheme Research Articles

Regional ACO-Based Cascaded Adaptive Routing for Traffic Balancing in Mesh-Based Network-on-Chip Systems

The regular topology of mesh-based network-on-chip (NoC) provides flexible and scalable architecture for chip multiprocessor (CMP) systems. However, as the complexity of network increases, routing problems become performance bottlenecks. In the field of wide area networks (WANs), ant colony optimization (ACO) has been applied to an adaptive routing for improving performance and achieving load balancing. Nevertheless, if we directly apply ACO to NoC systems, the implementation cost of ACO is excessively high. To overcome this problem, the ACO-based adaptive routing must be reformulated while considering both router cost and NoC efficiency. This work proposes the regional ACO-based cascaded adaptive routing (RACO-CAR) scheme with the following techniques: 1) table elimination by removing redundant information, 2) table sharing by grouping pheromone information to merge table content, and 3) cascaded routing that assigns traffic to different uncongested regions to balance traffic. Our experimental results demonstrate that the RACO-CAR scheme has an improvement of 3.9-36.84 percent in saturation throughput compared with existing adaptive routing schemes. The implementation cost of the RACO-CAR router is only 37.4 percent of that of the ACO-based router with full routing table. Therefore, the proposed RACO-CAR scheme has high area efficiency, defined as saturation throughput divided by the total cost of router.

Personalized routing for multitudes in smart cities

Human mobility in a city represents a fascinating complex system that combines social interactions, daily constraints and random explorations. New collections of data that capture human mobility not only help us to understand their underlying patterns but also to design intelligent systems. Bringing us the opportunity to reduce traffic and to develop other applications that make cities more adaptable to human needs. In this paper, we propose an adaptive routing strategy which accounts for individual constraints to recommend personalized routes and, at the same time, for constraints imposed by the collectivity as a whole. Using big data sets recently released during the Telecom Italia Big Data Challenge, we show that our algorithm allows us to reduce the overall traffic in a smart city thanks to synergetic effects, with the participation of individuals in the system, playing a crucial role.

Social-Insect-Inspired Networking for Autonomous Load Optimisation

The now established paradigm of System on Chip advances towards high-density many-core systems by employing Networks on Chip (NoCs) to connect a large number of processing elements. This brings many new challenges to embedded system design, but also opens up opportunities for new approaches that can leverage and exploit the many-core fabric in ways that traditional system architectures could not. This paper describes a new approach of adopting behavioural aspects of social insects as an inspiration towards autonomous, self-repairing systems. Each node in the NoC is considered as a member of a distributed colony and a simple adaptive controller is responsible for determining the behaviour of each node (member of the colony), relying only on a set of sensory inputs local to each node and small amounts of information shared between neighbours. Three adaptive routing schemes are presented that demonstrate how a sense-act-model applied at node level can lead to the emergence of novel routing behaviours that provide runtime self-optimisation of network load balancing without any prior analysis of the NoC topology. It is also discussed how these emergent behaviours of systems inspired by social insect colonies can be exploited to exhibit other novel autonomous and adaptive behaviours including fault tolerance and dynamic task allocation.

Adaptive Routing for Dynamic On-Body Wireless Sensor Networks

Energy is scarce in mobile computing devices including wearable and implantable devices in a wireless body area network. In this paper, an adaptive routing protocol is developed and analyzed which minimizes the energy cost per bit of information by using the channel information to choose the best strategy to route data. In this approach, the source node will switch between direct and relayed communication based on the quality of the link and will use the relay only if the channel quality is below a certain threshold. The mathematical model is then validated through simulations which shows that the adaptive routing strategy can improve energy efficiency significantly compared with existing methods.

Adaptive routing strategy on networks of mobile nodes

The design of routing strategies for networks of mobile nodes has received increasing attention in recent years. In this paper, we propose an adaptive routing strategy that incorporates geographical distance with local traffic information through a tunable parameter h. It is found that there exists an optimal value of h, leading to the maximum traffic throughput of the network. The optimal value of h decreases as the moving speed increases and increases as the communication radius increases. The dependence of the throughput on the moving speed and the communication radius is also studied. Our results show that for a wide range of the parameters, the throughput decreases as the moving speed increases. However, when the value of the parameter is set to be one, the maximum throughput is obtained at a moderate speed. Moreover, we find that the throughput increases with the communication radius.

Path-Congestion-Aware Adaptive Routing With a Contention Prediction Scheme for Network-on-Chip Systems

Network-on-chip systems can achieve higher performance than bus systems for chip multiprocessor systems. However, as the complexity of the network increases, the channel and switch congestion problems become major performance bottlenecks. An effective adaptive routing algorithm can help minimize path congestion through load balancing. However, conventional adaptive routing schemes only use channel-based information to detect the congestion status. Due to the lack of switch-based information, channel-based information is difficult to reveal the real congestion status along the routing path. Therefore, in this paper, we remodel the path congestion information to show hidden spatial congestion information and improve the effectiveness of routing path selection. We propose a path-congestion-aware adaptive routing (PCAR) scheme based on the following techniques: 1) a path-congestion-aware selection strategy that simultaneously considers switch congestion and channel congestion, and 2) a contention prediction technique that uses the rate of change in the buffer level to predict possible switch contention. The experimental results show that the proposed PCAR scheme can achieve a high saturation throughput with an improvement of 15.4%-48.7% compared to existing routing schemes. The proposed PCAR method also includes a VLSI architecture, which has higher area efficiency with an improvement of 16%-35.7% compared with the other router designs.

An Adaptive Threshold Routing Scheme in DTNs

The paper proposes an adaptive threshold routing scheme for delay tolerant networks. And it introduces the principle of ATM. The applications motivate a routing method that is different from Epidemic Routing Strategy in two ways: throughput and delivery. Finally the simulation results show that ATM obtains significant superior by comparing with the ERS.

Dynamic programming-based runtime thermal management (DPRTM)

Complex thermal behavior inhibits the advancement of three-dimensional (3D) very-large-scale-integration (VLSI) system designs, as it could lead to ultra-high temperature hotspots and permanent silicon device damage. This article introduces a new runtime thermal management strategy to effectively diffuse and manage heat throughout 3D chip geometry for a better throughput performance in networks on chip (NoC). This strategy employs a dynamic programming-based runtime thermal management (DPRTM) policy to provide online thermal regulation. Reactive and proactive adaptive schemes are integrated to optimize the routing pathways depending on the critical temperature thresholds and traffic developments. Also, when the critical system thermal limit is violated, an urgent throttling will take place. The proposed DPRTM is rigorously evaluated through cycle-accurate simulations, and results show that the proposed approach outperforms conventional approaches in terms of computational efficiency and thermal stability. For example, the system throughput using the DPRTM approach can be improved by 33% when compared to other adaptive routing strategies for a given thermal constraint. Moreover, the DPRTM implementation presented in this article demonstrates that the hardware overhead is insignificant. This work opens a new avenue for exploring the on-chip adaptability and thermal regulation for future large-scale and 3D many-core integrations.

Destination-based congestion awareness for adaptive routing in 2D mesh networks

The choice of routing algorithm plays a vital role in the performance of on-chip interconnection networks. Adaptive routing is appealing because it offers better latency and throughput than oblivious routing, especially under nonuniform and bursty traffic. The performance of an adaptive routing algorithm is determined by its ability to accurately estimate congestion in the network. In this regard, maintaining global congestion state using a separate monitoring network offers better congestion visibility into distant parts of the network compared to solutions relying only on local congestion. However, the main challenge in designing such routing schemes is to keep the logic and bandwidth overhead as low as possible to fit into the tight power, area, and delay budgets of on-chip routers. In this article, we propose a minimal destination-based adaptive routing strategy (DAR), where every node estimates the delay to every other node in the network, and routing decisions are based on these per-destination delay estimates. DAR outperforms Regional Congestion Awareness (RCA), the best previously known adaptive routing algorithm that uses nonlocal congestion state. The performance improvement is brought about by maintaining fine-grained per-destination delay estimates in DAR that are more accurate than regional congestion metrics measured in RCA. The increased accuracy is a consequence of the fact that the per-destination delay estimates are not corrupted by congestion on links outside the admissible routing paths to the destination. A scalable version of DAR, referred to as SDAR, is also proposed for minimizing the overheads associated with DAR in large network topologies. We show that DAR outperforms local adaptive routing by up to 79% and RCA by up to 58% in terms of latency on SPLASH-2 benchmarks. DAR and SDAR also outperform existing adaptive and oblivious routing algorithms in latency and throughput under synthetic traffic patterns on 8×8 and 16times;16 mesh topologies, respectively.

Adaptive Scheduling and Routing Scheme for Delay Guarantee in Wireless Sensor Networks

In wireless sensor networks (WSNs), periodical sleeping scheme on sensor nodes is an effective way to save energy. However, it will hinder the capability of the network to provide real-time data reporting due to relay node being sleep. Motivated by this, we propose an adaptive scheduling and routing scheme for guaranteeing dynamic end-to-end delay requirement while minimizing the energy consumption. First of all, we utilize an optimal wake-up scheduling algorithm to achieve the initial wake-up schedules and routes and design an adaptive adjustment algorithm. When the end-to-end delay requirement of a region changes, our proposed adaptive adjustment algorithm can locally adjust the wake-up schedules or the routing tables of the nodes which are the nearest ones to the source node, so as to minimize energy consumption and the impact on other regions while guaranteeing the new end-to-end delay requirement of the region. Through experiments in a real wireless sensor network and extensive simulations, we can get that the proposed scheme can conserve at least 20% energy consumption comparing to other existing adjustment algorithms, and its performance approaches that of the optimal solution.

Polynomial-time adaptive routing algorithm based on spectrum scan in dynamic flexible optical networks

Optical Orthogonal Frequency Division Multiplexing (OOFDM) has been proposed as a highly spectrum-efficient modulation technique, which can provide flexible spectrum assignment with fine granularity. In OOFDM-based flexible optical networks, Routing and Spectrum Assignment (RSA) has become a key problem. However, widely used dynamic RSA schemes, such as Fixed Routing (FR) and K-shortest Paths (KSP) routing schemes, are not able to realize route computation based on the link state information, thus leading to poor blocking performance and inefficient resource utilization. To solve this problem, Adaptive Routing (AR) schemes, e.g., the Entire Path Searching (EPS) scheme, have been proposed recently. These schemes have low blocking probability; however, since their computational complexities are factorial, they are not suitable for use in real networks. In this paper, we propose a novel Spectrum-Scan Routing (SSR) scheme in dynamic flexible optical networks. To the best of our knowledge, SSR is the first polynomial-time AR scheme that can realize adaptive shortest-route computation. Simulation results show that our proposed SSR scheme has lower blocking probability and higher resource utilization compared with FR and EPS. Moreover, the worst-case computational complexity of SSR increases linearly with the network scale of the torus topologies, making it applicable to real networks.

Adaptive Multi Path Routing Protocol for Heterogeneous Multi-Hop Wireless Sensor Network

Multi path routing protocol plays important part in the multi hop heterogeneous wireless sensor network. To get better performance, adaptive Wireless Senor Network Multi Path Routing Scheme (AMRH) is proposed, which is made up of three phrases: initial setup, route discovery and establishment, route maintenance. In the first phrase, every node gets the initial route table. In the second phrase, source node will find minimum-cost path among multiple paths. In the third phrase, route maintenance is conducted under adaptive mechanism. Simulation shows that AMRH scheme can prolong sensor network lifetime by 19.5%, increase data delivery ratio by 5.6%.

An adaptive routing approach for personal rapid transit

Personal Rapid Transit (PRT) is a public transportation mode, in which small automated vehicles transport passengers on demand. Central control of the vehicles leads to interesting possibilities for optimized routings. The complexity of the involved routing problems together with the fact that routing algorithms for PRT essentially have to run in real-time often leads to the choice of fast greedy approaches. The most common routing approach is arguably a sequential one, where upcoming requests are greedily served in a quickest way without interfering with previously routed vehicles. The simplicity of this approach stems from the fact that a chosen route is never changed later. This is as well the main drawback of it, potentially leading to large detours. It is natural to ask how much one could gain by using a more adaptive routing strategy. This question is the main motivation of this article. In this paper, we first suggest a simple mathematical model for PRT, and then introduce a new adaptive routing algorithm that repeatedly uses solutions to an LP as a guide to route vehicles. Our routing approach incorporates new requests in the LP as soon as they appear, and reoptimizes the routing of all currently used vehicles, contrary to sequential routing. We provide preliminary computational results that give first evidence of the potential gains of an adaptive routing strategy, as used in our algorithm.

PASS: An Adaptive Multi-Copy Routing Scheme for Intermittently Connected Mobile Ad Hoc Networks

PASS: An Adaptive Multi-Copy Routing Scheme for Intermittently Connected Mobile Ad Hoc Networks

A Novel Energy Efficient and Administrator Based Secured Routing in MANET

The lack of static infrastructure causes several issues in mobile Ad Hoc network , such as energy utilization, node authentication and secure routing. In this paper we propose a new scheme for energy efficient secure routing of data packets in MANET. This approach will reduce the computational overhead to make it more energy efficient than existing schemes. As there is no stationary infrastructure,each node in MANET acts a router that forwards data packets to other nodes. Therefore selection of effective, suitable, adaptive and robust routing scheme is of utmost importance. We have reduced the amount of network activity for each node required to route a data packet. This leads to lesser wastage of energy and increases security.Our simulation results will show how this is energy efficient and secure. Finally we have discussed how this scheme prevents various attacks which may jeopardize any wireless network.

Adaptive message size routing strategy for delay tolerant network

Delay tolerant network (DTN) is a kind of computer network that suffer from the frequent disconnections, network partitioned and unstable network connectivity, therefore maintaining an uninterrupted route from source to destination is not possible. Therefore, the transmission of message is achieved via intermediate nodes by adopting a novel transmission mechanism called store-carry and forward where node stores the incoming message in its buffer, carries it while moving and forward it when it comes in the transmission range of other nodes. DTN routing protocols can be either single copy or multi copy. In single copy protocols, the node forwards the unique copy of message along a single path. These protocols suffer the long delivery delay. In multi copy protocols, the node diffuses multiple copies of same message along dissimilar paths. Thus, message can reach destination via more than one path. However, the replication process consumes high volume of network resources such as buffer space, bandwidth and node energy. The probabilistic routing strategies for instance PRoPHET Protocol minimizes the consumption of resources and forwards a message to a custodian by using a metric of delivery probability. The probability describes the suitability of a node to meet the destination of message. However, when node mobility pattern is not symmetric the probabilistic computations cannot predict the accurate forwarding decision. In this paper, we have proposed a novel message forwarding strategy called Adaptive Message-Size Routing strategy (AMRS) by which a node handovers the copy of message to its neighboring nodes by using a metric named as mean threshold (MTH). We have compared the performance of AMRS with Epidemic and PRoPHET routing protocols. The proposed routing strategy has performed better in terms of maximizing delivery probability while minimizes message drops and number of transmissions.

Study on dynamic routing and spectrum assignment in bitrate flexible optical networks

The exponential growth of Internet traffic necessitates high-capacity optical networks and has also highlighted the importance of bandwidth-flexible and multi-granularity transport platforms. Improving both transport capacity and bandwidth flexibility is a significant challenge in optical networks. A bitrate flexible network architecture that is based on orthogonal frequency division multiplexing has been proposed as a promising solution for meeting this challenge. In the current study, we focus on the online routing and spectrum assignment problems in the aforementioned network architecture and introduce a general solution for dynamic bitrate flexible traffic in distributed environments. A novel spectrum representation method based on continuous spectrum segments is introduced into the networks. Segment-based routing and signaling mechanisms provide general solutions that support both the conventional slot-based networks and the ideal fully gridless networks. The routing algorithms and spectrum selection approaches are demonstrated and compared in a simulation. Performance estimation indicates that random spectrum segment assignment achieves the lowest capacity blocking rate in light traffic, whereas the adaptive routing plus minimum residual spectrum scheme obtains the lowest capacity blocking rate under heavy traffic.

An Efficient Adaptive Deadlock-Free Routing Algorithm for Torus Networks

A deadlock-free minimal routing algorithm called clue is first proposed for VCT (virtual cut-through)-switched tori. Only two virtual channels are required. One channel is applied in the deadlock-free routing algorithm for the mesh subnetwork based on a known base routing scheme, such as, negative-first or dimension-order routing. The other channel is similar to an adaptive channel. This combination presents a novel fully adaptive minimal routing scheme because the first channel does not supply routing paths for every source-destination pair. Other two algorithms named flow controlled clue and wormhole clue are proposed. Flow controlled clue is proposed for VCT-switched tori, which is fully adaptive minimal deadlock-free with no virtual channel. Each input port requires at least two buffers, each of which is able to keep a packet. A simple but well-designed flow control function is used in the proposed flow controlled clue routing algorithm to avoid deadlocks. Wormhole clue is proposed for wormhole-switched tori. It is partially adaptive because we add some constraints to the adaptive channels for deadlock avoidance. It is shown that clue and flow controlled clue work better than the bubble flow control scheme under several popular traffic patterns in 3-dimensional (3D) torus. In a wormhole-switched tori, the advantage of wormhole clue over Duato's protocol is also very apparent.

Exploiting the Burstiness of Intermediate-Quality Wireless Links

We address the challenge of link estimation and routing over highly dynamic links, thats is, bursty links that rapidly shift between reliable and unreliable periods of transmissions. Based on significant empirical evidence of over 100,000 transmissions over each link in 802.15.4 and 802.11 testbeds, we propose two metrics, expected future transmissions (EFT) and MAC3, for runtime estimation of bursty wireless links. We introduce a bursty link estimator (BLE) that based on these two metrics, accurately estimates bursty links in the network rendering them available for data transmissions. Finally, we present bursty routing extensions (BRE): an adaptive routing strategy that uses BLE for forwarding packets over bursty links if they offer better routing progress than long-term stable links. Our evaluation, comprising experimental data from widely used IEEE 802.15.4-based testbeds, reveals an average of 19% and a maximum of 42% reduction in the number of transmissions when routing over long-range bursty links typically ignored by routing protocols. Additionally, we show that both BLE and BRE are not tied to any specific routing protocol and integrate seamlessly with existing routing protocols and link estimators.

Adaptive Opportunistic Routing for Wireless Ad Hoc Networks

A distributed adaptive opportunistic routing scheme for multihop wireless ad hoc networks is proposed. The proposed scheme utilizes a reinforcement learning framework to opportunistically route the packets even in the absence of reliable knowledge about channel statistics and network model. This scheme is shown to be optimal with respect to an expected average per-packet reward criterion. The proposed routing scheme jointly addresses the issues of learning and routing in an opportunistic context, where the network structure is characterized by the transmission success probabilities. In particular, this learning framework leads to a stochastic routing scheme that optimally explores and exploits the opportunities in the network.