Route Optimization Research Papers - Academia.edu (original) (raw)

This paper presents a framework that develops algorithms for solving combined locational and multihop routing optimization problems. The objective is to determine resource node locations in a multiagent network and to specify the multihop routes from each agent to a common destination through a network of resource nodes that minimize total communication cost. These problems are computationally complex (NP-hard) where

- by
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- Distributed Computing, Routing, Network optimization, Maximum Entropy Principle

Most electronic manufacturing industries use computer numerical controlled (CNC) machines for drilling holes on printed circuit board (PCB). Some machines do not choose the optimal route when completing their tasks. Hence, this paper proposes an approach, which is based on ant colony system (ACS), for finding the optimal route in PCB holes drilling process. In ACS, an artificial ant starts to move from a random hole location and moves to the next hole location, based on the pheromone level between the locations of two holes. The higher the pheromones level, the higher the chance for the artificial ant to choose that path. At the same time, that ant deposits its pheromone on the path chosen. This process is repeated until the artificial ant builds a solution, which is evaluated with other artificial ants’ solutions. The best artificial ant deposits additional pheromone to its path. The best-found path is updated as the iteration continues. Experimental result indicates that the proposed ACS-based approach is capable to efficiently find the optimal route for PCB holes drilling process.

The main purpose of this work is to optimize cash flow in case of the encashment process in the ATM network with prediction of ATM refusal. The solution of these problems is based on some modified algorithms for the Vehicle Routing Problem and use statistical methods to compile the requests from the ATM network. A numerical example is considered.

- by Alyona Gubar and +1
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- Operations Research, Route Optimization, ATM networks, Statistical Methods

Raw materials play a vital role in the ferrochrome production using submerged arc furnace route. Optimized combination of different raw materials can improve the performance of furnace and minimize the power consumption. This process carries numerous process complexities as well as feed variation, which make it difficult to model mathematically. Artificial neural network known as a black box approach is attempted to predict the effect of various raw materials (pellets, briquettes, hard lumps, friable lumps, coke and quartzite) on the performance of submerged arc furnace by incorporating a production capability index (PCI). Production capability index is a ratio of the daily production and the maximum production achieved by the furnace in the ideal conditions. A detailed statistical analysis was carried on plant data to study relationship of raw material and furnace performance. In the first step of the study, the non-linear relationship between the raw material inputs and PCI is tried to predict by multivariable linear regression. Further feed forward back propagation neural network with three different learning algorithms were tried to improve the prediction accuracy (conjugant gradient decent, Levenberg-Marquardt optimization and resilient back propagation). Radial basis neural networks were also tried but no significant improvement was found in the performance prediction. The correlation coefficient is considered as a accuracy measure, and found that correlation between predicted and actual values were 0.64 for multilinear regression which was improved 0.70, 0.71 for radial basis neural network and feed forward neural network with resilient back propagation learning algorithm. Comparative analysis has been done among statistical analysis, neural network structures and the actual values of production capability index.

Waste Management (WM) obtains one third of its revenue from landfill disposals and two-thirds from wastecollection services. As most of the revenue comes from collecting trash, improving efficiency in operating the fleet improves the bottom line. After a flurry of acquisitions and a merger with USA Waste, WM found itself with a large fleet of vehicles whose routing, dispatching, maintenance, and management were decentralized. WM recognized that it could reduce operating costs by improving its use of assets. It contracted with the Institute of Information Technology to develop WasteRoute, a comprehensive route-management system that took into account WM's specific routing concerns and provided broad benefits. Initially, the target audience of the system was the dispatchers and indirectly the drivers. Sales and customer service also benefited because WasteRoute integrated the sales, customer service, and operations departments. The system reduced operating costs, provided better customer service, and determined appropriate prices. WM deployed WasteRoute across the nation beginning in March 2003. By the end of 2003, WM had 984 fewer routes, saving 18million.Itestimatedthatitssavingsfor2004duetothereductionwillbe18 million. It estimated that its savings for 2004 due to the reduction will be 18million.Itestimatedthatitssavingsfor2004duetothereductionwillbe44 million. As it extends the system to additional areas, it expects additional route reductions.

- by Byung-In Kim
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- Information Systems, Applied Mathematics, Waste Management, Business and Management

Waste Management has become a difficult task for Municipal Cooperation. It is observed that the practice of trash collection is quite inefficient and ineffective in most of the areas in India. This is due to the size of population, economical drawbacks and majorly because of the lack of feedback mechanisms. A proper well-designed system that monitors the filling of bins in a community will make the work easier for the trash collecting personnel. In this paper, a prototype of a Smart Bin Monitoring System is implemented with the help of ZigBee connectivity in a Star network, NodeMCU, Arduino UNO microcontroller and the weight and distance sensors. The software side of the project, is based on the waste fill status of each bin, an algorithm for optimized path is developed using MATLAB GUI. Also, the bin values and the monitored parameters are made accessible to the households and waste collectors via an APP developed using the MIT App Inventor.

- by IAEME Publication
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- Route Optimization, ZigBee, Matlab Gui, NodeMCU
- by sherif kamel
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- Wireless Communications, Computer Networks, Mobile IP, Route Optimization
- by Asrul Adam
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- Computational Intelligence, Swarm Intelligence, Routing, Particle Swarm Optimization

Solid waste collection remains the main concern in urban planning, involving engineering strategy and approach. Collection of solid waste, which takes 70-85% of total solid waste management cost, if being managed carelessly will result in longer travel distance and inefficient schedule design. The consequences are high cost management and air and river pollution. The main objective of this review paper is to collect information regarding solid waste collection and transportation in Ipoh and suggest a proper route optimization which emphasizes on recycling of generated solid waste. Solid waste recycling is one of the main components of integrated solid waste management (ISWM) which has not been practiced well in majority of the cities in Malaysia. Ipoh city consists of 22 zones, forming an area of 643 sq.km. The generation rate of 0.85 kg/capita per day is increasing by 5.4% per annum, a rapid increment of waste generated. A day-to-day assessment on the collection practices are highlighted which involve curb collection from house-to-house and backyard collection in industrial areas. Collector vehicles is parked overnight in a depot located in Buntong and will daily collect and dispose accumulated collected waste to a dumping site in Bercham. While all stages from collection and final disposal are finished in 5 hours, no integrated recycling activities were found in Ipoh due to lack of ISWM. Therefore, a new optimized route which provides specified time, crew and vehicles for collection of recyclables is suggested via application of Geographical Information System (GIS).

- by Amirhossein Malakahmad
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- Urban Planning, Recycling, Network Analysis, Transportation

Unmanned Aerial Vehicle (UAV) is defined as aircraft without the onboard presence of pilots. UAVs have been used to perform intelligence, surveillance, and reconnaissance missions. The UAVs are not limited to military operations, they can also be used in commercial applications such as telecommunications, ground traffic control, search and rescue operations, crop monitoring, etc. In this paper, we propose a swarm intelligence-based method for UAVs' route optimization. The team of UAVs is used for area coverage with the defined set of waypoints. The problem can be interpreted as a well-known Traveling Salesman Problem where the task is to find the route of minimal length such that all the waypoints are visited only once. We applied the Ant System algorithm and compared it with the Nearest Neighbor Search. The experimental results confirm the effectiveness of our method, especially for a large number of waypoints.

Agricultural producers seek to complete their field work operations as quickly as possible. This is achievable through the simultaneous use of multiple vehicles for an operation. However, path allocation and scheduling then must be considered. Transforming the field work problem into a Vehicle Routing Problem (VRP) and using optimization procedures designed for this problem provides a method of allocating paths. In this work, the accuracy of a VRP representation of field work is confirmed and the ability of this optimization system to reduce field work times is verified. Experiments were conducted using three tractors during a rotary mowing operation. First, the traditional routes used by human drivers were recorded. Then, a VRP representation of this operation was created, and new routes generated by a Tabu Search optimization procedure. Finally, the field operation was repeated using the optimized routes. Using these routes, the time to complete the field work was reduced by 17.3% and the total operating time for all tractors was reduced by 11.5%. The predictions by the VRP representation for completion time and total time were both within 2% of the actual times recorded when the tractors followed the computer-generated routes in the field. These reductions illustrated the ability of the route optimization procedure to improve effective field efficiency.

- by Hasan Seyyedhasani
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- Path planning, Vehicle Routing Problems, Route Optimization

Collaborative transportation and logistics pooling are relatively new concepts in research, but are very popular in practice. In the last years, collaborative transportation seems a good city logistics alternative to classical urban consolidation centres, but it is still in a development stage. This paper proposes a framework for urban logistics pooling ex-ante evaluation. This framework is developed with two purposes. The first is to generate comparable contrasted or progressive scenarios representing realistic situations; the second to simulate and assess them to make a "before-after" comparative analysis. In this framework, a demand generation model is combined with a route optimization algorithm to simulate the resulting routes of the proposed individual or collaborative distribution schemes assumed by each scenario. Then, several indicators can be obtained, mainly travelled distances, working times, road occupancy rates and operational monetary costs. To illustrate that framework, several scenarios for the urban area of Lyon (France) are simulated and discussed to illustrate the proposed framework possible applications.

- by Jesus Gonzalez
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- Resource sharing, Working Time, Route Optimization, Decision Support

This paper is the result of a research project developed by the DIGITI’s research group at Francisco José de Caldas University, on optimization problems by using artificial intelligence and it shows the implementation of
a genetic algorithm (GA) as a tool for planning and optimization transport tours, with the goal of finding the best path destinations for a fleet of vehicles. It presents basic concepts of the theory and the results obtained, about the administration and logistics in the supply chain, through a planning solution that optimizes the use of transportation resources.

- by Miroslaw Klinkowski and +2
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- Optimization Problem, Route Optimization, Optical Packet Switching, Analytical Model

In mobile IP based networks, most of the packet drops occur due to mobile handoff from one sub-network to another sub-network or larger delays in between sender and receiver due to encapsulation and tunnelling of packets. Packet loss during the handoff operation in mobile IP with route optimization and smooth handover will degrade the performance of Transmission Control Protocol (TCP). To prevent performance degradation due to mobile handover packet drops, a number of packet buffering and packet forwarding mechanisms have been proposed. However, mobile user continually change its point-of-attachment and can sometimes move into congested base station of foreign agent sub network, its buffered forwarded packets are likely to be dropped at the new base station. This can lead to decrease in congestion window size at the sender TCP, which will severely degrade the performance of TCP even though there is no congestion within the network. In this approach, hardware resources (packet buffers) are efficiently utilized, at the same time performance degradation of TCP due to congested base station of current mobile node is minimized through packet buffers, markers and with modification in Mobile IP binding update message.

- by Satish Anamalamudi
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- Congestion Control, Mobile Communication, Mobile IP, Route Optimization
- by Juan Gomez
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- Route Optimization, High speed networks, Wireless Ad Hoc Network

The goal of the paper is to present a decomposed approach to optimization of inter-domain routing in IP networks. A problem of maximizing the total amount of traffic carried in an inter-domain network is formulated as a linear programme. Using Lagrangean relaxation the problem is decomposed with respect to individual domains. A resolution method based on subgradient optimization combined with recovering of a near optimal primal solution is discussed. Effectiveness of the method for the case of synchronized local intra-domain computations is tested using two different subgradient optimization algorithms: a divergent series algorithm and a proximal bundle algorithm. The issue of implementing such a method in a distributed networkwide process of routing optimization which could be run in the control plane of the network using the existing EGP protocols is considered. Two schemes for such decomposed optimization involving only partial synchronization of local intra-domain computations are discussed.

- by M. Mycek and +1
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- Route Optimization, IP networks, Lagrangean relaxation

Lately, numerous nature inspired optimization techniques has been applied to combinatorial optimization problems, such as Travelling Salesman Problem. In this paper, we study the implementation of one of the nature inspired optimization techniques called Magnetic Optimization Algorithm in Travelling Salesman Problem. In this implementation, each magnetic agent or particle in Magnetic Optimization Algorithm represents a candidate solution of the Travelling Salesman Problem. The strength of the magnetic force between these particles is inversely proportion to the distance calculated by the Traveling Salesman Problems solution they represented. Particles with higher magnetic force will attract other particles with relatively lower magnetic force, towards it. The process repeated until satisfying a stopping condition, and the solution with lowest distance is considered as the best- found solution. The performance of the proposed approach is benchmarked with a case study taken from a well-known test bank.

This paper introduces an Intelligent Transport System we called SigFlot, which is specially designed for fleet management, using dynamic information. Its main objective is to optimally manage the resources of a transport enterprise in order to achieve a safer and more efficient transport. The system consists of one set of modules which perform different jobs: communications (GSM/SMS), location (GPS), hiring / info through the Web, geographic information (GIS), route optimizing (Dijkstra algorithm and Taboo search). This application is fully developed in Java so it eases its portability to other platforms and OS.

Lately, numerous nature inspired optimization techniques has been applied to combinatorial optimization problems, such as Travelling Salesman Problem. In this paper, we study the implementation of one of the nature inspired optimization techniques called Magnetic Optimization Algorithm in Travelling Salesman Problem. In this implementation, each magnetic agent or particle in Magnetic Optimization Algorithm represents a candidate solution of the Travelling Salesman Problem. The strength of the magnetic force between these particles is inversely proportion to the distance calculated by the Traveling Salesman Problem's solution they represented. Particles with higher magnetic force will attract other particles with relatively lower magnetic force, towards it. The process repeated until satisfying a stopping condition, and the solution with lowest distance is considered as the bestfound solution. The performance of the proposed approach is benchmarked with a case study taken from a well-known test bank.

An important requirement for Internet protocol (IP) networks to achieve the aim of ubiquitous connectivity is network mobility (NEMO). With NEMO support we can provide Internet access from mobile platforms, such as public transportation vehicles, to normal nodes that do not need to implement any special mobility protocol. The NEMO basic support protocol has been proposed in the IETF as a first solution to this problem, but this solution has severe performance limitations. This paper presents MIRON: Mobile IPv6 route optimization for NEMO, an approach to the problem of NEMO support that overcomes the limitations of the basic solution by combining two different modes of operation: a Proxy-MR and an address delegation with built-in routing mechanisms. This paper describes the design and rationale of the solution, with an experimental validation and performance evaluation based on an implementation.

Abstract—Lately, numerous nature inspired optimization techniques has been applied to combinatorial optimization problems, such as Travelling Salesman Problem. In this paper, we study the implementation of one of the nature inspired optimization techniques called Magnetic Optimization Algorithm in Travelling Salesman Problem. In this implementation, each magnetic agent or particle in Magnetic Optimization Algorithm represents a candidate solution of the Travelling Salesman Problem. The strength of the magnetic force between ...

A control device for periodic flash photographies is provided with an actuation timing setting circuit in which actuation timings of a camera are manually set and a timer control circuit which generates a first signal at every set actuation timing and a second signal a given period of time before every set actuation timing. The first signal is applied to a camera release electromagnet of the camera for a camera release operation. The second signal is applied to a voltage booster circuit of an electronic flash device or an external power source for an electronic flash device, so that a control transistor of the voltage booster circuit is made conductive by the second signal to supply current to the base of an oscillation transistor of the voltage booster circuit for the oscillation thereof, whereby the voltage booster circuit generates a high voltage applied to a main capacitor of the electronic flash device for the charging thereof. The generation of the second signal may stop after...

- by Chunming Rong
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- Internet Routing Protocol, Route Optimization, Home Network, Data Transmission

Abstract-Mobile IPv6 is the mobility protocol of the IPv6 protocol. The mobility feature in IPv6 is supposed to be default, but still there are obstacles carrying out deployment. Great needs for this new Internet Protocol are security, scalability, efficiency and the lack of IPv4 addresses. Deployment of ,this long needed new ,protocol has ,been delayed partly due to the route

- by Chunming Rong
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- Internet Routing Protocol, Route Optimization, Home Network, Data Transmission

Nowadays, researchers show more and more interests to Vehicular Ad hoc NETworks (VANETs), which are a specific instance of Mobile Ad hoc NETworks (MANETs) where nodes are vehicles. In VANETs, vehicles have no energy resource constraint which could extend coverage and network lifetime, but have a high mobility patterns that cause frequent and fast topology changes. Consequently, VANETs have particular research interests, like dedicated MAC and routing optimization. In our previous work, we have proposed MOvement Predictionbased Routing (MOPR) concept for VANETs, which improves the routing process by selecting the most stable route in terms of lifetime with respect to the movement of vehicles. And in this paper, we present how this MOPR concept can be applied to position-based routing protocols, and how it improves their performances. Based on simulation results we compare MOPR with the position-based routing protocol GPSR and another movement-based routing protocol called MORA.

- by Massimiliano Lenardi and +1
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- Wireless Communications, Mobile Ad Hoc Network, Route Optimization, Vehicular Network

We implement a two-stage DPCM coding scheme for wireless sensor networks. The scheme consists of temporal and spatial stages that compress data by making predictions based on samples from the past and helping sensors. It continuously monitors the additional gain provided by samples from other sensors, and therefore can be combined with data-centric routing algorithms for joint compression/routing optimization. Backward-NLMS adaptation is used to better track changing environments and avoid coefficient transmissions. Several simulations are conducted to demonstrate the effectiveness of this coding scheme.

- by Huiyu Luo
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- Computer Science, Data Compression, Routing, Wireless Sensor Networks

Route Optimization (RO) is an important feature of Electric Vehicles (EVs) navigation system. This work performs the RO for EVs using the Multi Constrained Optimal Path (MCOP) problem. The proposed MCOP problem aims to minimize the length of the path and meets constraints on travelling time, time delay due to traffic signals, recharging time and recharging cost. The optimization is performed through a design of Simulated Evolution (SimE) which has innovative goodness, allocation and mutation operations for the route optimization problem. The simulations show that the proposed algorithm has performance almost equal to or better than the Genetic Algorithm (GA) and it requires 0.5 (is the population size and ≥ 2 and generally = 20) times lesser memory than the GA.

- by Umair Siddiqi
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- Genetic Algorithms, Genetic Algorithm, Optimization, Navigation

In this paper, various decision support schemes are proposed evaluating the selection of different network infrastructures in terms of routing optimization and signal strength selection. Limited computational and radio communication capabilities require collaborative algorithms with energy-aware communication. Power saving makes it possible to guarantee basic levels of system performance, such as connectivity, throughput and delay, in the presence of both mobility-immobility and a large number of sensor nodes. A variety of approaches for intelligent energy-efficient schemes have been simulated over different performance metrics.

Summary Mobile IPv6 is a network-layer mobility protocol for the IPv6 Internet. Route optimization mechanism in IPv6 offers an efficient routing option to mobile IPv6 than that is available for mobile IPv4. The protocol includes security mechanisms, such as the return-routability tests for security of route optimization mechanism. This paper explains the threat model and existing security solutions for route optimization. An improved, robust and simple security solution is also presented based on IPSec, which is an inbuilt security feature of IPv6.

- by Majid Jamil
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- Internet Routing Protocol, Route Optimization, Home Agent

Mobile Ad-hoc Network (MANET) routing protocols and NEMO Basic Support are considered key technologies for vehicle networks. Cooperation between MANET and NEMO (MANEMO) brings several benefits especially for route optimization and multihoming. We made a real field vehicle communication environment with NEMO and MANET. By switching from NEMO to MANET, routes between vehicles are optimized and network performances improved in terms of latency and bandwidth. Experiment results show that network performances are further improved with simultaneous usage of NEMO and MANET. Network performances were shown on a web site in real time and mapped at locations using GPS information.

- by Manabu Tsukada
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- Mobile Ad Hoc Network, Manet, Route Optimization, Multihoming
- by Kevin Bassler
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- Applied Mathematics, Computer Science, Physics, Medicine

Manipulation of wire sizing, buffer sizing, and buffer insertion are a few techniques that can be used to improve very large scale integration (VLSI) circuit routing. This paper enhances an existing approach, which is based on Particle Swarm Optimization (PSO) for solving routing problem in VLSI circuits. A two-step Binary Particle Swarm Optimization (BPSO) approach is proposed in this study to obtain the best path of wire placement with buffer insertion from source to sink. The best path of wire placement is found in the first step by the first BPSO and then the second BPSO finds the best location of buffer insertion along the wire. The fitness function used for the second BPSO is the time delay formulated based on the iterative RLC delay model. A case study is taken to measure the performance of the proposed model and the result obtained.

- by Zainal Abidin
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- Engineering, Computer Science, Computational Intelligence, Iterative Methods

- by IAEME Publication
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- Route Optimization, ZigBee, Matlab Gui, NodeMCU

Time delay in very large scale integration circuit routing can be improved using several techniques such as intelligent selection of the size of wire and buffer, and strategic buffer placement.This paper proposes the use of Binary Particle Swarm Optimization to find the best selection of the size of wire and buffer, and ideal location of buffer insertion along the wire. For the proposed approach, a particle epresents a possible solution of the buffer placement problem. The time delay produced by the proposed solution of each particle is then calculated. The particle will try to improve its solution by trying to replicate its best record and swarm best record. The process is repeated until stopping condition is achieved. Swarm best record is taken as the best solution obtained by the proposed approach. A case study is taken to measure the performance of the proposed approach. The proposed approach has a good potential in VLSI routing and can be extended in future.

WSN, MPR, MPR-CDS, Graph split.

- by Ridha Ouni
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- Energy Consumption, Information, Route Optimization, Sensor Network

To provide fabless designers the same advantage as Integrated Device Manufacturer (IDMs), a design-oriented litho model has been calibrated and an automated lithography (litho) hotspot detection and fixing flow has been implemented during... more

- by Shyue Quek
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- Route Optimization, Model Calibration

The performance of very large scale integration (VLSI) circuits is depends on the interconnected routing in the circuits. In VLSI routing, wire sizing, buffer sizing, and buffer insertion are techniques to improve power dissipation, area usage, noise, crosstalk, and time delay. Without considering buffer insertion, the shortest path in routing is assumed having the minimum delay and better performance. However, the interconnect delay can be further improved if buffers are inserted at proper locations along the routing path. Hence, this paper proposes a heuristic technique to simultaneously find the optimal routing path and buffer location for minimal interconnect delay in VLSI based on particle swarm optimization (PSO). PSO is a robust stochastic optimization technique based on the movement and information sharing of swarms. In this study, location of doglegs is employed to model the particles that represent the routing solutions in VLSI. The proposed approach has a good potential in VLSI routing and can be further extended in future.

- by Mostafa Hani
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- Engineering, Computer Science, Computational Intelligence, Iterative Methods

In the present paper the Ant Colony Optimization (ACO) Algorithm is introduced for best routing identification applied in urban solid waste collection. The proposed solid waste management system is based on a geo-referenced Spatial Database supported by a Geographic Information System (GIS). The GIS takes account of all the required parameters for solid waste collection. These parameters involve static and dynamic data, such as positions of trash-cans, road network, related traffic and population density, In addition, time schedule of trash-collection workers and track capacities and technical characteristics are considered. ACO spatio-temporal statistical analysis model is used to estimate interrelations between dynamic factors, like network traffic changes in residential and commercial areas in a 24 hour schedule, and to produce optimized solutions. The user, in the proposed system, is able to define or modify all required dynamic factors for the creation of an initial scenario. By modifying these particular parameters, alternative scenarios can be generated leading to the several solutions. The Optimal solution is identified by a cost function that takes into account various parameters, for instance labor and equipment costs as well as social implications.

—This paper focuses on sensor data management in the Solar Car Optimized Route Estimation (SCORE) system which is currently being developed. The data collection is split into two phases: the a priori phase related to the environment and the real time phase related to the solar vehicle. The hardware and software architecture for a priori phase is illustrated in detail, while the real time phase is discussed as a part of the embedded car computer. The full system description for SCORE is presented with guidelines for the future work and implementation of it.

- by Harun Siljak and +1
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- Electric Vehicles, Solar Energy, Route Optimization, Solar-powered Cars
- by Sumanta Pyne
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- Distributed Computing, Fuzzy Logic, Wireless networks, Performance Evaluation

The route optimization operation in Mobile IP Version 6 (MIPv6) allows direct routing from any correspondent node to any mobile node and thus eliminates the problem of "triangle routing" present in the base Mobile IP Version 4 (MIPv4) protocol. Route optimization, however, requires that a mobile node constantly inform its correspondent nodes about its new care-of addresses by sending them binding update messages. Unauthenticated or malicious binding updates open the door for intruders to perform redirect attacks, i.e., malicious acts which redirect traffic from correspondent nodes to locations chosen by intruders. How to protect binding update messages to defend against redirect attacks is a challenging problem given the open environment in which MIPv6 operates. In this paper, we first look at two solutions proposed by the IETF Mobile IP Working Group and point out their weaknesses. We then present a new protocol for securing binding update messages. We also show that our protocol achieves strong security and at the same time is highly scalable to wide spread deployment.

- by feng bao
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- Mobile IP, Route Optimization, Authenticated Key Exchange, Mobile Node

This paper presents MARS, a novel multilevel full-chip gridless routing system. The multilevel framework with recursive coarsening and refinement allows for scaling of our gridless routing system to very large designs. The downward pass of recursive coarsening builds the representations of routing regions at different levels while the upward pass of iterative refinement allows a gradually improved solution. We introduced a number of efficient techniques in the multilevel routing scheme, including resource reservation, graph-based Steiner tree heuristic and history-based iterative refinement. We compared our multilevel framework with a recently published three-level routing flow . Experimental results show that MARS helps to improve the completion rate by over 10%, and the runtime by 11.7×.

- by Jie Fang
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- Iterative Methods, Routing, VLSI, Computer Hardware

The restricted resource based sensor network, can be optimized at different level. The route optimization is one of the methods to improve the resource utilization and effective network communication. In this paper, a multi-featured route optimization is provided using ACO approach. At the earlier stage of this work, random ANT agents are distributed over the network with coverage constraints. Each ANT analyzed the sensor devices under energy, distance and direction parameters. Based on these parameters, the effective node in each ANT regions will be identified. In the final stage, the backward ANT is processed to generate the optimized path.

- by IJCSMC Journal
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- Route Optimization

Network Mobility (NEMO) Basic Support Protocol enables mobile networks to change their point of attachment to the Internet, while preserving established sessions of the nodes within the mobile network. NEMO basic solution is an extension of Mobile IPv6 and it is based on tunnelling, which leads to suboptimal routing, packet overhead and latency, especially when nesting (i.e. a mobile network that contains other mobile networks within) is involved. In this article we present a route optimisation solution for mobile networks based on Mobile IPv6. The goal is to use the route optimisation support for Mobile IPv6 available in the Correspondent Nodes to provide route optimisation for mobile networks. The solution also supports nested mobile networks without requiring additional tunnelling, thus reducing packet overhead and latency with regard to Network Mobility basic solution.

- by Maria Teresa Calderón
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- Route Optimization, Network Mobility, Mobile Network