Performance evaluation of efficient multi-objective evolutionary algorithms for design space exploration of embedded computer systems

Multi-objective evolutionary algorithms (MOEAs) have received increasing interest in industry because they have proved to be powerful optimizers. Despite the great success achieved, however, MOEAs have also encountered many challenges in real-world applications. One of the main difficulties in applying MOEAs is the large number of fitness evaluations (objective calculations) that are often needed before an acceptable solution can be found. There are, in fact, several industrial situations in which fitness evaluations are computationally expensive and the time available is very short. In these applications efficient strategies to approximate the fitness function have to be adopted, looking for a trade-off between optimization performance and efficiency. This is the case in designing a complex embedded system, where it is necessary to define an optimal architecture in relation to certain performance indexes while respecting strict time-to-market constraints. This activity, known as design space exploration (DSE), is still a great challenge for the EDA (electronic design automation) community. One of the most important bottlenecks in the overall design flow of an embedded system is due to simulation. Simulation occurs at every phase of the design flow and is used to evaluate a system which is a candidate for implementation. In this paper we focus on system level design, proposing an extensive comparison of the state-of-the-art of MOEA approaches with an approach based on fuzzy approximation to speed up the evaluation of a candidate system configuration. The comparison is performed in a real case study: optimization of the performance and power dissipation of embedded architectures based on a Very Long Instruction Word (VLIW) microprocessor in a mobile multimedia application domain. The results of the comparison demonstrate that the fuzzy approach outperforms in terms of both performance and efficiency the state of the art in MOEA strategies applied to DSE of a parameterized embedded system.     

An adaptive overlay network inspired by social behaviour

Nature is a great source of inspiration for scientists, because natural systems seem to be able to find the best way to solve a given problem by using simple and robust mechanisms. Studying complex natural systems, scientists usually find that simple local dynamics lead to sophisticated macroscopic structures and behaviour. It seems that some kind of local interaction rules naturally allow the system to auto-organize itself as an efficient and robust structure, which can easily solve different tasks. Examples of such complex systems are social networks, where a small set of basic interaction rules leads to a relatively robust and efficient communication structure. In this paper, we present PROSA, a semantic peer-to-peer (P2P) overlay network inspired by social dynamics. The way queries are forwarded and links among peers are established in PROSA resemble the way people ask other people for collaboration, help or information. Behaving as a social network of peers, PROSA naturally evolves to a small world, where all peers can be reached in a fast and efficient way. The underlying algorithm used for query forwarding, based only on local choices, is both reliable and effective: peers sharing similar resources are eventually connected with each other, allowing queries to be successfully answered in a really small amount of time. The resulting emergent structure can guarantee fast responses and good query recall.     

Visual extraction of information from web pages

In this paper we present a graphical software system that provides an automatic support to the extraction of information from web pages. The underlying extraction technique exploits the visual appearance of the information in the document, and is driven by the spatial relations occurring among the elements in the page. However, the usual information extraction modalities based on the web page structure can be used in our framework, too. The technique has been integrated within the Spatial Relation Query (SRQ) tool. The tool is provided with a graphical front-end which allows one to define and manage a library of spatial relations, and to use a SQL-like language for composing queries driven by these relations and by further semantic and graphical attributes.     

A multi-objective evolutionary approach to image quality/compression trade-off in JPEG baseline algorithm

The JPEG algorithm is one of the most used tools for compressing images. The main factor affecting the performance of the JPEG compression is the quantization process, which exploits the values contained in two tables, called quantization tables. The compression ratio and the quality of the decoded images are determined by these values. Thus, the correct choice of the quantization tables is crucial to the performance of the JPEG algorithm. In this paper, a two-objective evolutionary algorithm is applied to generate a family of optimal quantization tables which produce different trade-offs between image compression and quality. Compression is measured in terms of difference in percentage between the sizes of the original and compressed images, whereas quality is computed as mean squared error between the reconstructed and the original images. We discuss the application of the proposed approach to well-known benchmark images and show how the quantization tables determined by our method improve the performance of the JPEG algorithm with respect to the default tables suggested in Annex K of the JPEG standard.     

Analysis of the maximum level policy in a production-distribution system

We consider a production-distribution system, where a facility produces one commodity which is distributed to a set of retailers by a fleet of vehicles. Each retailer defines a maximum level of the inventory. The production policy, the retailers replenishment policies and the transportation policy have to be determined so as to minimize the total system cost. The overall cost is composed by fixed and variable production costs at the facility, inventory costs at both facility and retailers and routing costs. We study two different types of replenishment policies. The well-known order-up to level (OU) policy, where the quantity shipped to each retailer is such that the level of its inventory reaches the maximum level, and the maximum level (ML) policy, where the quantity shipped to each retailer is such that the inventory is not greater than the maximum level. We first show that when the transportation is outsourced, the problem with OU policy is NP-hard, whereas there exists a class of instances where the problem with ML policy can be solved in polynomial time. We also show the worst-case performance of the OU policy with respect to the more flexible ML policy. Then, we focus on the ML policy and the design of a hybrid heuristic. We also present an exact algorithm for the solution of the problem with one vehicle. Results of computational experiments carried out on small size instances show that the heuristic can produce high quality solutions in a very short amount of time. Results obtained on a large set of randomly generated problem instances are also shown, aimed at comparing the two policies.     

Dynamic SLAs management in service oriented environments

The increasing adoption of service oriented architectures across different administrative domains, forces service providers to use effective mechanisms and strategies of resource management in order for them to be able to guarantee the quality levels their customers demands during service provisioning. Service level agreements (SLA) are the most common mechanism used to establish agreements on the quality of a service (QoS) between a service provider and a service consumer. The WS-Agreement specification, developed by the Open Grid Forum, is a Web Service protocol to establish agreements on the QoS level to be guaranteed in the provision of a service. The committed agreement cannot be modified during service provision and is effective until all activities pertaining to it are finished or until one of the signing party decides to terminate it. In B2B scenarios where several service providers are involved in the composition of a service, and each of them plays both the parts of provider and customer, several one-to-one SLAs need to be signed. In such a rigid context the global QoS of the final service can be strongly affected by any violation on each single SLA. In order to prevent such violations, SLAs need to adapt to any possible needs that might come up during service provision. In this work we focus on the WS-Agreement specification and propose to enhance the flexibility of its approach. We integrate new functionality to the protocol that enable the parties of a WS-Agreement to re-negotiate and modify its terms during the service provision, and show how a typical scenario of service composition can benefit from our proposal.