Kazuyuki Miyakita

Theoretical Analysis of Route Expected Transmission Count in Multi-Hop Wireless Networks

In multi-hop wireless networks, communication quality depends on the route from a source to a destination. In this paper, we consider a one-dimensional multi-hop wireless network where nodes are distributed randomly and theoretically analyze the relation between communication quality and routing policy using a measure called the Expected Transmission Count (ETX), which is the predicted number of data transmissions required to send a packet over that link, including retransmissions. First, we theoretically analyze the mean length of links, the mean number of hops, and the mean route ETX, which is the sum of the ETXs of all links in a route, of Longest Path Routing (LPR), and Shortest Path Routing (SPR). Second, we propose Adjustable Routing (AR), an approximation to Optimum Routing (OR), which minimizes route ETX. We theoretically compute the above characteristic values of AR. We also theoretically compute a lower bound of the mean route ETX of OR. We compare LPR, SPR, and OR using the results of analyses and show differences between these algorithms in the route ETX.

Modeling of a charging network for electric vehicles

This paper considers a network problem in charging infrastructure for electric vehicles (EVs). It generally takes a longer time to charge the empty battery of an EV than refueling of gasoline vehicles. It is not easy to actually reduce the waiting time for charging. However, if charging is done during shopping or eating, the charging time is no longer the waiting time. Of course, we may sometimes have to wait a longer time to charge batteries than shopping time to prevent running out of the batteries during the next drive. This means that we have a trade off between the extra waiting time and possibility to run out of battery. In this paper, we theoretically consider properties of this trade off and theoretically analyze characteristics of the extra waiting time needed to guarantee that an EV does not run out of battery in a drive. We discuss effects of some factors such as density of charging stations, the number of outlets in each station, the number of waiting cars, and so on.

Analysis and Relative Evaluation of Connectivity of a Mobile Multi-Hop Network

SUMMARY In mobile multi-hop networks, a source node S and a destination node D sometimes encounter a situation where there is no multihop path between them when a message M, destined for D, arrives at S. In this situation, we cannot send M from S to D immediately; however, we can deliver M to D after waiting some time with the help of two capabilities of mobility. One of the capabilities is to construct a connected multi-hop path by changing the topology of the network during the waiting time (Capability 1), and the other is to move M closer to D during the waiting time (Capability 2). In this paper, we consider three methods to deliver M from S to D by using these capabilities in different ways. Method 1 uses Capability 1 and sends M from S to D after waiting until a connected multi-hop path appears between S and D. Method 2 uses Capability 2 and delivers M to D by allowing a mobile node to carry M from S to D. Method 3 is a combination of Methods 1 and 2 and minimizes the waiting time. We evaluate and compare these three methods in terms of the mean waiting time, from the time when M arrives at S to the time when D starts receiving M, as a new approach to connectivity evaluation. We consider a one-dimensional mobile multi-hop network consisting of mobile nodes flowing in opposite directions along a street. First, we derive some approximate equations and propose an estimation method to compute the mean waiting time of Method 1. Second, we theoretically analyze the mean waiting time of Method 2, and compute a lower bound of that of Method 3. By comparing the three methods under the same assumptions using results of the analyses and some simulation results, we show relations between the mean waiting times of these methods and show how Capabilities 1 and 2

Theoretical Analysis of Pure Waiting Time for Battery Charging While Doing Something

Recently, Electric Vehicle (EV) is considered as one of important technologies of smart grid, however, there are some problems for spreading EVs. One of these problems is that charging the battery of an EV needs a longer time than refueling of gasoline vehicles. To overcome these problems, for example, some local governments in Japan started projects in which restaurants and shops rent outlets for charging EV of their customers while doing something such as eating or shopping. Under such projects, if an EV driver knows information on chargers such as the locations of chargers and the mean waiting times for using chargers, the driver may be able to reduce the time spent only for charging (pure waiting time). In this paper, we theoretically analyze the mean of the pure waiting time in cases where drivers know and do not know the above information. From the numerical results, we discuss what information is important to reduce the pure waiting time.

Relation between the number of broadcasts of probe packets and energy consumption in multi-hop wireless networks

In multi-hop wireless networks, if we know the packet reception rates of all links in the network, we can find the path with the minimum energy consumption. However, to obtain the packet reception rates with high accuracy, we need a number of exchanges of probe packets. Also, the energy consumption along a path depends on a routing method. In this paper, we consider three routing methods and evaluate the relation between the number of broadcasts of probe packets and the total energy consumption along the paths selected by these methods.

THEORETICAL ANALYSIS OF MEAN WAITING TIME FOR MESSAGE DELIVERY IN LATTICE AD HOC NETWORKS

In ad hoc networks, the analysis of connectivity performance is crucial. The waiting time to deliver message M from source S to destination D is a measure of connectivity that reflects the effects of mobility, and some approximate methods have been proposed to theoretically analyze the mean waiting time in one-dimensional ad hoc networks that consist of mobile nodes moving along a street. In this paper, we extend these approximate methods to analyze the mean waiting time in two-dimensional networks with a lattice structure with various flows of mobile nodes. We discuss how the mean waiting times behave in such complicated street networks and how to approximate two kinds of mean waiting times. We show that our approximate methods can successfully compute the mean waiting times for even traffic patterns and roughly estimate them for uneven traffic patterns in two-dimensional lattice networks. In these analyses, we consider two shadowing models to investigate how shadowing affects the waiting time. We also discuss the effect of different positions of S on the mean waiting time.

Theoretical analysis of minimum route ETX in two-dimensional random multi-hop wireless networks

In multi-hop wireless networks, we often encounter a situation where there are some candidate paths between source node S and destination node D, and have to choose a path from the candidates. Although ordinary routing protocols select paths with minimum hops, QoS (Quality of Service) routing protocols evaluate paths using measures of QoS, such as expected transmission count (ETX). In multi-hop wireless networks with QoS routing, it is an important issue to identify and characterize the best path from the viewpoint of network design. To do this, in [1], we proposed an approximate method to theoretically compute minimum route ETX in static one-dimensional random multi-hop wireless networks, and in [2], we theoretically identified the best path and gave an exact formula to compute minimum route ETX in static lattice multi-hop wireless networks. In this paper, we propose a new approximate method to theoretically analyze minimum route ETX in a two-dimensional random network. In this method, we extend the approximate method proposed in [1] to be used for two-dimensional random networks. We show this approximate method well describes minimum route ETX by comparing the numerical results of the theoretical methods and simulation results.