Reducing the Parameter Count through a Sensitivity Analysis Performed on a Mathematical Model Used for Estimating Energy Consumption in a Passive House

AbstractEnergy efficiency in the buildings sector is one of the main research areas on which the European Union has focused its efforts. Reducing energy consumption has become a priority, as well as its estimation and prediction. There are a number of different models used to achieve the latter, from white-box models (fully informed) to black-box models (all necessary information is inferred from data), as well as hybrid approaches. However, these existing gray-box models rely on mathematical models which can easily be over-parameterized. We have implemented a gray-box model and propose an improved Sensitivity Analysis method which we have used to identify the correlated parameters. Moreover, upon analyzing the results of this analysis, we propose a simplification applied on the mathematical model, without actually modifying it

Design and Development of a UDP-Based Connection-Oriented Multi-Stream One-to-Many Communication Protocol, Journal of Telecommunications and Information Technology, 2012, nr 1

A communication protocol is a set of rules defined formally that describes the format of digital messages and the rules for exchanging those messages in or between computing systems. The Internet Protocol Suite used for communications throughout the Internet uses encapsulation to provide a way of abstracting protocols and services. This abstraction is grouped into layers of general functionality. For protocols on the transmission layer, many choices exist. But while popular protocols such as TCP, UDP and SCTP do provide connection oriented communication offering reliability, ordering and data integrity, solutions that offer such connections from one point to multiple endpoints are still limited. TCP only supports point-to-point communication and SCTP offers multi-homing functionality, but the transmission is still limited to two logical endpoints. In this paper we use the simple, stateless, transmission model of UDP in order to provide TCP-like services for one-to-many communication that is not limited to just multi-homing or other particular solutions. The protocol supports reliable communication from one endpoint to multiple endpoints in different transmission modes. In order to make it easier for developers to customize the protocol to their needs and possibly extend/modify it in order to create new variants from it, the protocol is developed in user space. Because of this design restriction performance wasn’t the main objective of our work, but rather the ease of customization and experimentation with new protocol variants. The protocol was implemented in the C++ programming language using classes with virtual members. New variants of components, such as packet retransmission, can easily be implemented without changing the whole code base

HSO: A Hybrid Swarm Optimization Algorithm for Re-Ducing Energy Consumption in the Cloudlets

Mobile Cloud Computing (MCC) is an emerging technology for the improvement of mobile service quality. MCC resources are dynamically allocated to the users who pay for the resources based on their needs. The drawback of this process is that it is prone to failure and demands a high energy input. Resource providers mainly focus on resource performance and utilization with more consideration on the constraints of service level agreement (SLA). Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers’ information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. The cost functions will cover energy, performance and reliability concerns. With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). The simulation studies also showed a reduction in the number of required calculations by about 20% by the inclusion of the presented algorithms compared to the traditional static approach. There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. Conclusively, an energy-aware optimization model which describes the required system constraints was presented in this study, and a further proposal for techniques to determine the best overall solution was also made

Towards a Highly Available Model for Processing Service Requests Based on Distributed Hash Tables

This work aims to identify techniques leading to a highly available request processing service by using the natural decentralization and the dispersion power of the hash function involved in a Distributed Hash Table (DHT). High availability is present mainly in systems that: scale well, are balanced and are fault tolerant. These are essential features of the Distributed Hash Tables (DHTs), which have been used mainly for storage purposes. The novelty of this paper’s approach is essentially based on hash functions and decentralized Distributed Hash Tables (DHTs), which lead to highly available data solutions, which a main building block to obtain an improved platform that offers high availability for processing clients’ requests. It is achieved by using a database constructed also on a DHT, which gives high availability to its data. Further, the model requires no changes in the interface, that the request processing service already has towards its clients. Subsequently, the DHT layer is added, for the service to run on top of it, and also a load balancing front end, in order to make it highly available, towards its clients. The paper shows, via experimental validation, the good qualities of the new request processing service, by arguing its improved scalability, load balancing and fault tolerance model

Towards a Highly Available Model for Processing Service Requests Based on Distributed Hash Tables

This work aims to identify techniques leading to a highly available request processing service by using the natural decentralization and the dispersion power of the hash function involved in a Distributed Hash Table (DHT). High availability is present mainly in systems that: scale well, are balanced and are fault tolerant. These are essential features of the Distributed Hash Tables (DHTs), which have been used mainly for storage purposes. The novelty of this paper’s approach is essentially based on hash functions and decentralized Distributed Hash Tables (DHTs), which lead to highly available data solutions, which a main building block to obtain an improved platform that offers high availability for processing clients’ requests. It is achieved by using a database constructed also on a DHT, which gives high availability to its data. Further, the model requires no changes in the interface, that the request processing service already has towards its clients. Subsequently, the DHT layer is added, for the service to run on top of it, and also a load balancing front end, in order to make it highly available, towards its clients. The paper shows, via experimental validation, the good qualities of the new request processing service, by arguing its improved scalability, load balancing and fault tolerance model