Scalability and robustness of a market-based network resource allocation system

In this paper, we consider issues related to scalability and robustness in designing a market-based multi-agent system that allocates bandwidth in a communications network. Specifically, an empirical evaluation is carried out to assess the system performance under a variety of design configurations in order to provide an insight into network deployment issues. This extends our previous work in which we developed an application that makes use of market-based software agents that compete in decentralised marketplaces to buy and sell bandwidth resources. Our new results show that given a light to moderate network traffic load, partitioning the network into a few regions, each with a separate market server, gives a higher call success rate than by using a single market. Moreover, a trade-off in the number of regions was also noted between the average call success rate and the number of messages received per market server. Finally, given the possibility of market failures, we observe that the average call success rates increase with an increasing number of markets until a maximum is reached

Examination of Profitability in the Context of Bangladesh Banking Industry

Loans are the riskiest asset of a bank, but these loans play a pivotal role in banks' profitability. Banks 'profitability depends on the results of some parameters and among themBank b Return on Equity, Market Size, Market Concentration Index, and Bank RiskMeasure are widely used and the same are investigated in the Bangladesh Banking Industry in this study for a period of the last six years. The data comes from the annual reports of individual banks listed in Dhaka Stock Exchange (DSE) and from the Bangladesh bankb published statistics book (Scheduled Banks Statistics). Correlation matrix and stepwise regression have been used for the purpose of data analysis. The analysisfinds that market concentration and bank b risk do little to explain bank b return on equity, whereas bankb market size is the only variable providing an explanation for banks return on equity in the context of Bangladesh

Hypothalamic AgRP-neurons control peripheral substrate utilization and nutrient partitioning

Obesity-related diseases such as diabetes and dyslipidemia result from metabolic alterations including the defective conversion, storage and utilization of nutrients, but the central mechanisms that regulate this process of nutrient partitioning remain elusive. As positive regulators of feeding behaviour, agouti-related protein (AgRP) producing neurons are indispensible for the hypothalamic integration of energy balance. Here, we demonstrate a role for AgRP-neurons in the control of nutrient partitioning. We report that ablation of AgRP-neurons leads to a change in autonomic output onto liver, muscle and pancreas affecting the relative balance between lipids and carbohydrates metabolism. As a consequence, mice lacking AgRP-neurons become obese and hyperinsulinemic on regular chow but display reduced body weight gain and paradoxical improvement in glucose tolerance on high-fat diet. These results provide a direct demonstration of a role for AgRP-neurons in the coordination of efferent organ activity and nutrient partitioning, providing a mechanistic link between obesity and obesity-related disorders

Resource allocation in communication networks using market-based agents

This work describes a system that allocates end-to-end bandwidth, in a switched meshed communications network. The solution makes use of market-based software agents that compete in a number of decentralised marketplaces to buy and sell bandwidth resources. Agents perform a distributed depth first search with decentralised markets in order to allocate routes for calls. The approach relies on a resource reservation and commit mechanism in the network. Initial results show that under a light network load, the system sets up a high percentage of calls which is comparable to the optimum value and that, under all network loads, it performs significantly better than a random strategy

Resource Allocation in Communications Networks Using Market-Based Agents

The work in this thesis describes a system that allocates the end-to-end bandwidth, in a meshed communications network, to set up calls. The solution makes use of market-based software agents that compete in a number of decentralised market-places in order to buy and sell bandwidth. The network is partitioned into regions, where each has a separate market server from where the bandwidth resources are allocated. Agents perform a distributed search with decentralised markets in order to allocate routes for calls. The approach relies on a resource reservation and commit mechanism in the network. Results show that for a typical network given a light load, the system sets up 95% of calls and is comparable in performance to an instantaneous global search, which assumes complete knowledge of resource availability and sets up 97% of calls at the same load. As the network load is increased to a typical intermediate level, the system gives an average call success rate which is 76% of that given by the instantaneous global search. Furthermore, under all network loads, the system performs significantly better than a random strategy. We also consider issues associated with scalability and robustness in our multi-agent system. Specifically, an empirical evaluation was carried out to assess the system performance under a variety of design configurations in order to provide an insight into network deployment issues. This took place using networks that were fixed in size but which were scaled up with respect to the number of regions and, hence, market servers. We investigated two main measures: the average call success rate and average message load per market server, as the number of markets were increased in the network. The same investigations were performed in the presence of single market failures. For both the failure and non-failure cases, a trade-off was found between the two measures to find an optimum number of regions to deploy in the network. In general, results showed that in the absence of failures, fewer regions gave a higher average call success rate and more regions meant that, on average, market servers received less messages per market server, when searching for resources across a single regional route. With a single market failure, we saw that when more regions were deployed, in general, the average call success rate was higher up to a certain point and the number of messages received per market server was lower, when also using a single regional route. In the final part of this thesis, we make a change to part of our original algorithm in order to try and improve upon the system performance. To overcome the need for receiving fewer messages per market server and having quicker call set up times, we allow buyer agents to bid for resource bundles that lead to several boundary nodes in a region, in a single auction, rather than the possibility of using multiple auctions. Thus, we introduce a multi-destination buyer strategy. By constraining the amount of resource searching in this way, we can see that there are performance trade-offs where call set up times decrease, average call success rates increase in general, but that the system allocates a smaller proportion of longer distance calls than when using the original strategy. We also show that, in general, it is better to search across a single regional route instead of searching across multiple regional routes, particularly when the network load is high. However, at much lighter network loads, searching for resources by means of traversing alternative regions can give a better overall average call success rate

Scalability and robustness of a network resource allocation system using market-based agents

Abstract. In this paper, we consider issues associated with scalability and robustness in designing a market-based multi-agent system that allocates bandwidth in a communications network. Specifically, an empirical evaluation is carried out to assess the system performance under a variety of design configurations in order to provide an insight into network deployment issues. This extends our previous work in which we developed an application that makes use of market-based software agents that compete in decentralised marketplaces to buy and sell bandwidth resources in a network that is partitioned into regions, each with a separate market server. We investigate the average call success rate and average message load per market server, as the number of markets are scaled up in a fixed size network. The same investigations are performed in the presence of single market failures. Finally, for both the failure and non-failure cases, a trade-off is found between their average call success rates and message load per server in order to find an optimum number of regions to deploy in the network

Scalability and robustness of a market-based network resource allocation system

In this paper, we consider issues related to scalability and robustness in designing a market-based multi-agent system that allocates bandwidth in a communications network. Specifically, an empirical evaluation is carried out to assess the system performance under a variety of design configurations in order to provide an insight into network deployment issues. This extends our previous work in which we developed an application that makes use of market-based software agents that compete in decentralised marketplaces to buy and sell bandwidth resources. Our new results show that given a light to moderate network traffic load, partitioning the network into a few regions, each with a separate market server, gives a higher call success rate than by using a single market. Moreover, a trade-off in the number of regions was also noted between the average call success rate and the number of messages received per market server. Finally, given the possibility of market failures, we observe that the average call success rates increase with an increasing number of markets until a maximum is reached. 1

Examination of profitability in the context of Bangladesh Banking industry

Loans are the riskiest asset of a bank, but these loans play a pivotal role in banks\u27 profitability. Banks \u27profitability depends on the results of some parameters and among them Bank b Return on Equity, Market Size, Market Concentration Index, and Bank RiskMeasure are widely used and the same are investigated in the Bangladesh Banking Industry in this study for a period of the last six years. The data comes from the annual reports of individual banks listed in Dhaka Stock Exchange (DSE) and from the Bangladesh bankb published statistics book (Scheduled Banks Statistics). Correlation matrix and stepwise regression have been used for the purpose of data analysis. The analysisfinds that market concentration and bank b risk do little to explain bank b return on equity, whereas bankb market size is the only variable providing an explanation for banks return on equity in the context of Bangladesh

PTC&B Construction of Genetic Map of Jute (Corchorus olitorius L.) Based on RAPD Markers

The first and preliminary genetic linkage map of the jute genome was constructed with RAPD markers using two parents (Variety O-9897 and Accession No. 1805) and their F2 populations. Linkage analysis at a LOD (Log of odds base 10) score of 3.0 and a maximum distance 50 cM revealed 18 linkage groups. Among the 18 linkage groups, 15 contained single locus and the remaining three groups 16, 17 and 18 contained 2, 11 and 12 loci, respectively. The three multi locus linkage groups varying in length from 15.9- 241.7 cM, snapped a total length of 463.7 cM with an average marker density of 19.6 cM between adjacent markers. The basic chromosome number of Corchorus spp. is seven (2n = 14), so in saturated map, seven linkage groups should have been obtained to represent the genome. But for linkage group analysis, the effort was very limited and the total number of loci (40) was also low

Scalability and robustness of a network resource allocation system using market-based agents

agent, communications network, market, resource allocation, scalability, robustness,