Routing Phase Research Articles

A hybrid RFD-ACO approach for routing optimization in VLSI physical design

The rapid growth in VLSI design has set forth a number of challenges. With the ever-increasing number of transistors in a chip, reducing power consumption of the chip while retaining or increasing the efficiency at the same time has been a major priority for the designers. Optimizing the Routing phase in the VLSI design cycle is a very viable option to meet the challenge. Reducing wire-lengths as well as the number of vias in turn results in reduction of the capacitance of the chip and hence power consumption. Nature inspired algorithms (Swarm Intelligence) like Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), etc. have proved to be very promising in this field. In this paper, a relatively newer variant of the ACO called River Formation Dynamics (RFD) which removes some of the limitations of the original ACO algorithm has been combined with ACO to form a Hybrid model to deal with the routing problem at hand.

Enhancement of DSR and AODV Protocols Using Link Availability Prediction

Routing in wireless ad hoc networks is highly affected by its dynamic topology and power constrained mobile devices. Several routing protocols like proactive, reactive, hybrid, geographical, etc. have been proposed in the literature. Ineffectiveness of any routing protocol in such networks is caused due to the ignorance of link availability during the routing phase. In this paper, we proposed two link availability prediction techniques which are performed during routing of control packets. The first technique referred as zone based estimation, divides the transmission range area of every node into three zones namely inner, middle and outer, based on the received signal strength. Here, nodes lying in the inner and outer zone are prohibited from the control packet transmission as they have extremely high and low received signal strength, respectively. Nodes in the middle region are only allowed for the control packet flow within the locality. The second technique is an improvement over zone based estimation, where nodes in the outer zone are considered for route selection and is referred as segment based estimation. It calculates node’s link availability ratio for each adjacent links based on the current available position of the neighbor, its adjoining segment and sector where the neighbor is present within the transmission region of the node. This information assist in the control packet transfer within the outer zone. Simulation has been performed over DSR and AODV protocols in terms of control overhead bandwidth, number of control packets, route length and number of route errors generated in the network. The results show that the knowledge of link status during routing phase helps to find more stable routes with reduced control overhead and hence increases the overall network performance.

A joint routing and channel assignment in multi-radio multi-channel wireless mesh networks

To reduce inter-link interference and balance networks loads, this paper presents and evaluates a cross-layer algorithm for multi-radio multi-channel wireless mesh networks (WMNs), while conducting routing channel assignments. In channel assignment phase, we propose a greedy algorithm based on a multi-radio multi-channel interference model and select the channel with minimum of interference degree. In the routing phase, a new routing parameter which comprehensively considers interference, delay, load balancing and other factors is proposed. The new algorithm is compared with existing algorithm that is multi-radio multi-channel WMN based on ad hoc on-demand distance vector routing (MRMC-AODV) to illustrate the advantages. When the load reaches 6 Mbps, the throughput exceeds 14% of the MRMC-AODV, with a delay of nearly 80% of the MRMC-AODV latency and it reduces packet loss ratio by about 12%. The simulation results show that this algorithm can effectively improve the network throughput, reduce delay and decrease packet loss ratio.

An Augmented Routing Algorithm for Trusted Detection of Link Failures in MANETs

Now a days, the communication between different nodes in a Mobile Ad hoc Network (MANET) is not guarded. Various encryption mechanisms are used to protect the communication between nodes. Link failures and packet dropping due to unfaithful nodes are becoming one of the main opposition for the trusted detection of malicious nodes. A failure can occur either due to channel errors or harmful nodes in network. These attacks may have the intention of modifying the routing protocol so that the data transmission through a specific node controlled by the attacker disturbs the network topology. Thus it deteriorates the performance of network. Mutual association of dropped packets is capitalized for synthesizing the suspicious nodes in MANET. The algorithm proposed is using an efficient cryptosystem with cipher text list validator scheme and a communal auditing scheme for the validation of certificate received from individual nodes. For constructing the framework, the proposed algorithm with five phases has a network setup phase, data routing phase, communal auditing phase, error node detection phase and a data receiver phase. This framework makes the MANET node build a safe routing topology by effectively judging the harmful nodes as well as the unfaithful information accepted from supplementary nodes.

FH-OAOS

With the sharp increase of very large-scale integrated (VLSI) circuit density, we are faced with many knotty issues. Particularly in the routing phase of VLSI physical design, the interconnection effects directly relate to the final performance of circuits. However, the optimization capability of traditional rectilinear architecture is limited; thus, both academia and industry have been devoted to nonrectilinear architecture in recent years, especially octilinear architecture, which is the most promising because it can greatly improve the performance of modern chips. In this article, we design FH-OAOS, an obstacle-avoiding algorithm in octilinear architecture, by constructing an obstacle-avoiding the octilinear Steiner minimal tree (OAOSMT). Our approach first constructs an obstacle-free Euclidean minimal spanning tree (OFEMST) on the given pins based on Delaunay triangulation (DT). Then, two lookup tables about OFEMST’s edge are generated, which can be seen as the information center of FH-OAOS and can provide information support for algorithm operation. Next, an efficient obstacle-avoiding strategy is proposed to convert the OFEMST into an obstacle-avoiding octilinear Steiner tree (OAOST). Finally, the generated OAOST is refined to construct the final OAOSMT by applying three effective strategies. Experimental results on various benchmarks show that FH-OAOS achieves 66.39 times speedup on average, while the average wirelength of the final OAOSMT is only 0.36% larger than the best existing solution.

CARE: Heuristics for two-stage multi-product inventory routing problems with replenishments

The integration of distribution and routing constitutes the Inventory Routing Problem (IRP), an important aspect of Vendor Managed Inventory (VMI) systems. IRP involves decisions on timing of deliveries, sizes of shipments and routing of vehicles. In the context of supply chain collaboration, the scope of IRP expands to include replenishments at the depot. This paper studies an IRP involving multiple products from different suppliers, a central depot (CD) and a set of warehouses. We develop an integrated Integer Linear Programming (ILP) model to determine the optimal replenishments from suppliers to the CD as well as the routing schedules of vehicles from CD to the multiple warehouses over the defined time horizon. We propose an extended three-phase heuristic called CARE (Clustering, Allocation, Routing -Extended). In the heuristic, the replenishment schedules, from suppliers to the CD (for multiple products in the defined time horizon), is solved using a dynamic programming (DP) model. The routing schedules of vehicles from CD to the multiple warehouses is then modeled and solved as a capacitated IRP (CIRP) problem. With the replenishment schedules as an input from the DP model, the CIRP is solved in three-phases: Cluster the nodes, Allocate to these nodes and Route delivery vehicles through clusters of nodes. Three variants of heuristics are proposed based on the changes to the routing phase – CARE1, CARE2, and CARE3. Computational results for a broad range of test instances yield promising results and show usefulness of the solution approaches. Particularly, the proposed heuristics outperformed CPLEX upper bounds for larger problems with lesser computational effort. The average improvement obtained by the heuristics over CPLEX upper bounds for 15 and 20 warehouse problems, respectively, are: CARE1 – 0.94% and 3.6%, CARE2 – 1.36% and 4.26%, CARE3 – 2.87% and 6.08%. We also show that the results from the proposed heuristic are statistically better than the CPLEX upper bounds. The proposed approaches can easily be implemented into existing VMI systems.

Particle swarm optimization for maximizing lifetime of wireless sensor networks

Particle swarm optimization (PSO) is a popular bio-inspired algorithm which is applied to solve various optimization problems in many areas including machine intelligence, data mining, robotics and computer networks. In this paper, we propose a PSO-based scheme to solve hot spot problem caused by multi-hop communication in a cluster-based wireless sensor network. The scheme consists of routing and clustering algorithms which are shown to be energy efficient. In the routing phase, traffic load over the cluster heads (CHs) is evenly distributed, whereas in the clustering phase, we take care of all the CHs whose energy is exhausted fast by assigning lesser number of sensor nodes. In addition to this, we also develop a distributed scheme to prevent the CHs from their quick death which is resulted from complete energy depletion. We perform extensive simulation on the proposed algorithms and compare the results with some existing algorithms to demonstrate its strength.

Simulation Based Comparison Between OWL and DSDV

Mobile ad-hoc network is collection of mobile nodes like laptops; cell phones which have limited processing power and limited battery power also have limited bandwidth. MANET is self-adjustable with dynamic topology network, because of its mobile environment, routing face challenges. Main challenges in routing are to maximize delivery ratio and minimize End-to-End delay with minimum use of nodes resources, because mobile nodes have limited batter power and bandwidth. DSDV is proactive type routing protocol which trying to minimize route discovery time by manage route information in routing table and broadcast to other neighbors. OWL is a reactive routing protocol which uses DFS instead of broadcasting of RREQ to all its neighbors. In this paper we are going to compare these two routing protocol on the basis of their power consumption in different phases of routing.

FuzzRoute

The high density of interconnects, closer proximity of modules, and routing phase are pivotal during the layout of a performance-centric three-dimensional integrated circuit (3D IC). Heuristic-based approaches are typically used to handle such NP-complete problems of global routing in 3D ICs. To overcome the inherent limitations of deterministic approaches, a novel methodology for multi-objective global routing based on fuzzy logic has been proposed in this article. The guiding information generated after the placement phase is used during routing with the help of a fuzzy expert system to achieve thermally efficient and congestion-free routing. A complete global routing solution is designed based on the proposed algorithms and the results are compared with selected fully established global routers, namely Labyrinth, FastRoute3.0, NTHU-R, BoxRouter 2.0, FGR, NTHU-Route2.0, FastRoute4.0, NCTU-GR, MGR, and NCTU-GR2.0. Experiments are performed over ISPD 1998 and 2008 benchmarks. The proposed router, called FuzzRoute , achieves balanced superiority in terms of routability, runtime, and wirelength over others. The improvements on routing time for Labyrinth, BoxRouter 2.0, and FGR are 91.81%, 86.87%, and 32.16%, respectively, for ISPD 1998 benchmarks. It may be noted that, though FastRoute3.0 achieves fastest runtime, it fails to generate congestion-free solutions for all benchmarks, which is overcome by the proposed FuzzRoute of the current article. It also shows wirelength improvements of 17.35%, 2.88%, 2.44%, 2.83%, and 2.10%, respectively, over others for ISPD 1998 benchmarks. For ISPD 2008 benchmark circuits it also provides 2.5%, 2.6%, 1 %, 1.1%, and 0.3% lesser wirelength and averagely runs 1.68×, 6.42×, 2.21×, 0.76×, and 1.54× faster than NTHU-Route2.0, FastRoute4.0, NCTU-GR, MGR, and NCTU-GR2.0, respectively.

Introducing a preliminary consists selection in the locomotive assignment problem

The Locomotive Assignment Problem (LAP) is a class of planning and scheduling problems solved by assigning a fleet of locomotives to a network of trains. In the planning versions of the LAP, the type of consist (a group of linked locomotives) assigned to each train in a given schedule is determined. We introduce an optimization model (called consists selection) that precedes the planning LAP solution and determines the set of consist types. This selection leads to solutions that are characterized by potential savings in terms of overall fueling cost and are easier to handle in the routing phase.

A Real-Time Routing Protocol with Controlled Dissemination of Data Queries by Mobile Sink in Wireless Sensor Networks

Objective: One of the challenges faced in wireless sensor networks is the constraints in battery power. The main objective of this paper is to address the energy efficiency issue by proposing a real-time routing protocol with controlled dissemination of data queries by mobile sink (RTCD). Methodology: Two phases namely the flooding phase and the routing phase are followed for data collection by mobile sink. A mobile sink helps in efficient data gathering compared to a static sink, reducing the total energy consumption in the network. In the flooding phase, controlled dissemination is achieved by limiting the network diameter and setting a threshold value for residual energy of the nodes. In the routing phase, routing of data is done on the basis of choosing an optimal forwarder having the maximum weighted value of composite link metric, comprising the parameters Packet Reception Rate (PRR), packet one-hop velocity and residual energy of the nodes. Realtime data delivery ensures delivery of packets within deadlines in delay- constrained applications. Findings: Simulations using Network Simulator-2 suggest that the routing phase in RTCD outperforms the reactive, proactive and hybrid routing protocols in terms of QoS parameters such as Packet Delivery Ratio (PDR), Normalized Energy Consumption (NEC) and average end-to-end delay. The reactive, proactive and hybrid routing protocols considered are AODV, DSDV and ZRP respectively. It has been found that PDR for RTCD routing is higher than comparative protocols for large networks. RTCD routing gives intermediate results in case of average end-to-end delay and NEC. Also, the impact of network diameter on Total Energy Consumption (TEC) has been studied which shows that TEC increases with network diameter. An optimum value of 1.8J is set as the threshold value of residual energy of nodes based on the simulation results for controlling the energy consumption.

Fuzzy multi-objective programming algorithm for vehicle routing problems with backhauls

The vehicle routing problem with backhauls (VRPB) is an extension of the standard vehicle routing problem. VRPB has two sets of customers: linehaul customers and backhaul customers. The aim of this study is to propose a new algorithm based on fuzzy multi-objective programming (FMOP-VRPB algorithm) to solve the VRPB. The FMOP-VRPB algorithm has three phases; clustering, routing and local search. In the clustering phase, customers are assigned to vehicles by the proposed multi-objective programming (MOP) model with two objective functions: minimizing the total distance and maximizing the total savings value. The proposed MOP model is solved by fuzzy operators. The weights of the objectives are also calculated by a fuzzy two-person zero-sum game with mixed strategies using membership functions in a fuzzy pay-off matrix. In the routing phase, each vehicle is routed as a traveling salesman problem with backhauls. The local search phase is used to improve the routes.The primary contributions of the FMOP-VRPB algorithm are to consider the two objectives, to determine the weights of objectives using the proposed fuzzy pay-off matrix in the clustering phase and to use only mathematical programming in both the clustering and routing phases through many customers in an acceptable CPU time. The algorithm will also show that the proposed MOP model defines the seed customers itself in the clustering phase and will always generates feasible clusters, contrary to the reports in the literature.Benchmark problems from the literature are solved to test the performance of the FMOP-VRPB algorithm. The results indicate that the FMOP-VRPB algorithm generates sufficient solutions, and CPU times are within acceptable limits. In addition, a weekly routing problem for a logistics department of a ceramics firm in Turkey is solved by the FMOP-VRPB algorithm. Additionally, this study is the first to solve a real world VRPB; the solution shows that the FMOP-VRPB algorithm is suitable and effective for real world problems.

A Fault-Aware Toolchain Approach for FPGA Fault Tolerance

As the size and density of silicon chips continue to increase, maintaining acceptable manufacturing yields has become increasingly difficult. Recent works suggest that lithography techniques are reaching their limits with respect to enabling high yield fabrication of small-scale devices, thus there is an increasing need for techniques that can tolerate fabrication time defects. One candidate technology to help combat these defects is reconfigurable hardware. The flexible nature of reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs), makes it possible for them to route around defective areas of a chip after the device has been packaged and deployed into the field. This work presents a technique that aims to increase the effective yield of FPGA manufacturing by re-claiming a portion of chips that would be ordinarily classified as unusable. In brief, we propose a modification to existing commercial toolchain flows to make them fault aware. A phase is added to identify faults within the chip. The locations of these faults are then used by the toolchain to avoid faults during the placement and routing phase. Specifically, we have applied our approach to the Xilinx commercial toolchain flow and evaluated its tolerance to both logic and routing resource faults. Our findings show that, at a cost of 5--10% in device frequency performance, the modified toolchain flow can tolerate up to 30% of logic resources being faulty and, depending on the nature of the target application, can tolerate 1--30% of the device's routing resources being faulty. These results provide strong evidence that commercial toolchains not designed for the purpose of tolerating faults can still be greatly leveraged in the presence of faults to place and route circuits in an efficient manner.

PERFORMANCE OF TOPOLOGY AWARE RELIABLE ROUTING PROTOCOL FOR LARGE SCALE VIRTUAL PRIVATE NETWORK

A network which merges the usage of the public and the private networks and uses security software for the purpose of compressing, encrypting and masking the digital packets that are being transmitted in the network is called as Virtual Private Network (VPN). In VPN, the communication between the user ends is maintained such that it appears as if the source end is directly linked to the destination end over a concealed leased line. The private network, VPN uses the public network such as internet to link the remote locations with the users. In this study, we propose a new reliable protocol called as Topology Aware Reliable Routing Protocol (TARRP) for large scale VPN and compare its performance with the traditional protocol, Boarder Gateway Protocol (BGP). In this protocol, the communication between the end to end nodes takes place in two phases: Routing phase and authentication phase. In the routing phase, the upstream and the downstream routing paths are determined by the source node using the topology learning protocol. Based on the dynamic failure information of links, the sender selects the failure-free path towards the destination. In the authentication phase, the VPN gateway authenticates the packet before it is transmitted through the core. Thus, this technique efficiently allows the packet to be transmitted with ensured security. By simulation results, we show that our proposed protocol is better than the traditional routing protocol of VPN.

A distributed algorithm for energy efficient and fault tolerant routing in wireless sensor networks

Energy conservation and fault tolerance are the most two important challenging issues for the development of large scale wireless sensor networks (WSNs). Failure of cluster heads in a cluster based WSN is more catastrophic as they are responsible not only for data aggregation and transmission of the aggregated data to the base station but also relaying data for multi-hop communication. Therefore, a routing algorithm in WSNs should be energy aware as well as fault tolerant. In this paper, we present a distributed energy efficient and fault tolerant routing algorithm for WSNs. The algorithm selects next-hop cluster head in energy efficient manner in the data routing phase and carefully restores the connectivity of the neighbours of a cluster head in case of its failure. The algorithm is tested extensively by considering several scenarios of WSN. The experimental results are compared with the existing algorithms in terms of several metrics to show the effectiveness of the proposed algorithm.

A Node-based Mathematical Model towards the Location Routing Problem with Intermediate Replenishment Facilities under Capacity Constraint

In this paper, we study the location routing problem with intermediate replenishment facilities (LRPIRF), an extension of the location routing problem (LRP), where the vehicles can replenish at some intermediate facilities. Vehicles leave the depot with load on-board, serve customers until out of load, may return to an intermediate facility to replenish, and finally return to the depot, completing their route. In this paper, we initiate a mathematical mixed integer programming model with new kind of subtour elimination constraints for this problem. Moreover, the facility location phase is considered besides vehicle routing phase in our problem. The objective of the problem is to find routes for vehicles to serve all customers at a minimal cost in terms of total travel cost and total facility location cost, without violating the capacity constraint of the vehicles. The solution to the LRPIRF is obtained through CPLEX solver in commercial software GAMS 23.5.1 ,Genetic Algorithm and Tabu Search algorithm. Computational results are obtained on a set of randomly generated instances and indicate the effectiveness of the proposed algorithms in terms of solution time and quality.

A Flow-Partitioned Unequal Clustering Routing Algorithm for Wireless Sensor Networks

Energy efficiency and energy balance are two important issues for wireless sensor networks. In previous clustering routing algorithms, multihop transmission, sleep scheduling, and unequal clustering are always used to improve energy efficiency and energy balance. In these algorithms, only the cluster heads share the burden of data forwarding in each round. In this paper, we propose a flow-partitioned unequal clustering routing (FPUC) algorithm to achieve better energy efficiency and energy balance. FPUC consists of two phases: clustering and routing. In the clustering phase, the competition radius is computed according to the node density and the distance from sensor nodes to the sink. The sensor nodes that have more residual energy and larger overlapping degree have higher probability to be selected as cluster heads. In the routing phase, each cluster head first finds the gateway nodes and then distributes the data flow to each of its gateway nodes depending on residual energy. After that, each gateway node forwards the data to the next hop with minimum cost. Two metrics called network lifetime and coverage lifetime are used to compare the performance of FPUC with that of the existing ones. Simulation results show that FPUC can achieve longer network lifetime and coverage lifetime than previous algorithms.

Robust node-disjoint multipath routing for wireless sensor networks

In wireless sensor networks WSNs, disjoint multipath routing has gotten immense research interest due to its capability of providing high reliability and load balancing. In this paper, we present a robust node-disjoint multipath routing RNMR protocol for WSNs. The protocol first constructs a multi-routing tree which has a number of node-joint but link-disjoint subtrees, and then finds multiple paths along these subtrees. Furthermore, by taking advantage of the structural characteristics inherent in the multi-routing tree, we present a customised redundancy scheme to improve the reliability of data transmission. The scheme provides individualised data redundancy for each sensor node. The protocol does not need to employ any control beacons in the data routing phase. Theoretical analysis and simulation results show that our protocol achieves higher reliability, reduces end-to-end delay and improves energy efficiency compared with existing approaches.

Converge-and-Diverge: A Geographic Routing for Delay/Disruption-Tolerant Networks Using a Delegation Replication Approach

Routing in delay/disruption-tolerant networks (DTNs) is without the assumption of contemporaneous end-to-end connectivity to relay messages. Geographic routing is an alternative approach using real-time geographic information instead of network topology information. However, if considering the mobility of destination, its real-time geographic information is often unavailable due to sparse network density in DTNs. Using historical geographic information to overcome this problem, we propose the converge-and-diverge (CaD) by combining two routing phases that depend on the proximity to the movement range estimated for destination. The key insight is to promote message replication converging to the edge of this range and diverging to the entire area of this range to achieve fast delivery, given limited message lifetime. Furthermore, the concept of delegation replication (DR) is explored to overcome the limitation of routing decisions and the local maximum problem. Evaluation results under the Helsinki city scenario show an improvement of CaD in terms of delivery ratio, average delivery latency, and overhead ratio. Since geographic routing in DTNs has not received much attention, apart from the design of CaD, our novelty also focuses on exploring DR to overcome the limitation of routing decision and the local maximum problem, in addition to enhancing efficiency, as DR originally intended.

Fine-grained multi-phase array designs

Hybrid multiprocessor architectures which combine re-configurable computing and multiprocessors on a chip are being proposed to transcend the performance of standard multi-core parallel systems. Both fine-grained and coarse-grained parallel algorithm implementations are feasible in such hybrid frameworks.A compositional strategy for designing fine-grained multi-phase regular processor arrays to target hybrid architectures is presented in this paper. The method is based on deriving component designs using classical regular array techniques and composing the components into a unified global design. Effective designs with phase-changes and data routing at run-time are characteristics of these designs. In order to describe the data transfer between phases, the concept of communication domain is introduced so that the producer–consumer relationship arising from multi-phase computation can be treated in a unified way as a data routing phase. This technique is applied to derive new designs of multi-phase regular arrays with different dataflow between phases of computation.