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The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

In many cases it is not appropriate to utilise a system of daily route scheduling. This paper looks at the situation where a fixed route system is required and the demand characteristics of the customers must be matched to the system.

Order picking, the assembly of a customer’s order from items in storage, is an essential link in the supply chain and is the major cost component of warehousing. The critical issue is to simultaneously reduce the cost and increase the speed of the order picking activity. The main objectives are to: evaluate various routeing policies in a random storage environment; evaluate the impact of warehouse shape and pick‐up/drop‐off location; and examine the interaction of the routeing policies, warehouse shape, and pick‐up/drop‐off location under different pick list sizes. The experimental results clearly indicate that the optimal routeing procedure generates significantly shorter routes than heuristic methods. The composite and largest gap routeing policies are, however, significantly better than simpler heuristic procedures. Further testing, in addition, indicates that the shape of the warehouse and the location of the pick‐up/drop‐off point can affect the picking efficiency.

A lot of recent research has been focused on developing network mobility management to support the movement of a mobile network consisting of several mobile nodes. The IETF NEMO working group proposed the NEMO basic support protocol that defines a methodology for supporting such network mobility using bi‐directional tunneling between the home agent and the mobile router. However, this protocol has been found to suffer from the so‐called ‘dog‐leg problem’, and despite alternative research efforts to solve this problem, there are still limitations in the efficiency of real time data transmission and intra‐domain communication. Accordingly, the current paper proposes a new route optimization methodology that uses unidirectional tunneling and a tree‐based intra‐domain routing mechanism. As such, the proposed scheme can provide faster signaling and data transmission and be easily extended to support micro‐mobility without any additional extensions. The performance of the proposed scheme is also evaluated to demonstrate its efficiency.

The purpose of this paper is to provide the method and system to conduct online measurement and the characterization of temperature during printed circuit board (PCB) routing process as well as the optimization of router design based on the investigation of routing temperature.

The background of this research is introduced first. Then the method to measure the routing temperature on-line by using an infrared camera is presented. The routing process is characterized by investigating the routing temperature. Tool design optimization is conducted based on the temperature in processing PCB with aluminum substrate. Finally the concluding remarks of this research are presented.

The routing temperature can be accurately measured by an infrared camera. Routing temperature is sensitive to properties of PCB, types of router and routing parameters. Very high temperature is experienced if non-appropriate routers are used to process board with aluminum substrate. It is demonstrated by the experiments that two fluted tool, three fluted tool and coated tool with three flutes are suitable for aluminum substrate processing by considering the low temperature and the nice surface finish.

The paper highlights the key points to measure the routing temperature on-line by an infrared camera and characterize the routing process and optimize the tool design by investigating the measured temperature as well.

Order picking, the activity by which a number of goods are retrieved from a warehousing system to satisfy a number of customer orders, is an essential link in the supply chain and is the major cost component of warehousing. The critical issue is to simultaneously reduce the cost and increase the speed of the order picking activity. The main objectives of this paper are: evaluate various routing heuristics and an optimal routine in a volume‐based and random storage environment; compare the performance of volume‐based storage to random storage; and examine the impact of travel speed and picking rates on routing and storage policy performance. The experimental results show the solution gap between routing heuristics and optimal routing is highly dependent on the travel speed and picking rate, the storage policy, and the size of the pick list. In addition, volume‐based storage produced significant savings over random storage, but again these savings are dependent on the travel speed and picking rate.

The main objective of this paper is to introduce the development of a novel feature recognition system for escape route planning. The genetic algorithm (GA) can be a useful tool in solving route planning problems.

A computer‐aided design (CAD) system is proposed to help to predict the best escape route. The system is based on a feature recognition process, which will scan a CAD drawing to determine the centroid points of corridors, and determine the best escape route with the help of GA.

The feature recognition system provides a quick method of determining the available pathways for use in escape route planning.

Factors such as multiple story buildings, number of occupants, or fire spread are not considered. Thus the system will be useful in the initial stages of escape route planning.

The system is limited to perpendicular walls, which should be of the same thickness. Doorways should also be a constant size. Thus the system will be useful in determining where escape routes exist, and attempt to determine the best route based on that information.

This paper shows how legacy drawings from various CAD systems may be reused to plan escape routes, rather than creating new drawings for the same purpose. This is useful to those in escape route planning, since the redrawing of plans using custom software is inefficient.

Increasingly, companies are looking for more efficient ways of distributing their goods and are turning to Computer‐assisted Vehicle Routeing Systems (CAVRS) to replace manual routeing systems. The aim of CAVRS is to reduce the cost of distribution without adversely affecting service. A framework of criteria developed to evaluate CAVRS packages is described, based on the proposed characteristics of an “ideal” CAVRS. The criteria represent the most important aspects that should be considered by potential users when selecting a package.