jMetal is a Java-based framework for multi-objective optimization using metaheuristics. It is a flexible, extensible, and easy-to-use software package that has been used in a wide range of applications. In this paper, we describe the design issues underlying jMetal, focusing mainly on its internal architecture, with the aim of offering a comprehensive view of its main features to interested researchers. Among the covered topics, we detail the basic components facilitating the implementation of multi-objective metaheuristics (solution representations, operators, problems, density estimators, archives), the included quality indicators to assess the performance of the algorithms, and jMetal's support to carry out full experimental studies.

The jMetal framework for multi-objective optimization: Design and architecture

A comprehensive review of the data replication techniques in the cloud environments

MORM: A Multi-objective Optimized Replication Management strategy for cloud storage cluster

Routing in Wireless Sensor Networks (WSNs) is the most significant and the challenging issue for the researchers in terms of enhancing its performance in terms of network lifetime, energy efficiency, scalability, connectivity, throughput, etc. They have the incredible capability to interact and gather data from any physical environment with help of routing protocols. Many routing protocols based solutions have been proposed in the recent years for accomplishing the preferred level of performance in WSNs for these issues. The hierarchical heterogeneous cluster based energy efficient routing protocols are more efficient as compared to flat and location based routing protocols due to the presence of nodes heterogeneity in terms of energy level of sensor nodes which enhances the lifetime of the network. The most recent trend that extensively enhances the functionality and the performance of WSNs is the use of mobile sensor nodes. In this paper, the authors proposed a novel concept regarding mobile sensor nodes is proposed called Mobile Energy Aware Cluster Based Multi-hop (MEACBM) routing protocol for hierarchical heterogeneous WSNs which selects CHs on the basis of newly proposed probability equation which selects only that sensor node as Cluster Head (CH) which has the highest energy among other sensor nodes by introducing a new term S(i).E in the equation. It considers hierarchical heterogeneous clustering considering three levels of sensor nodes; multi-hoping for inter-cluster communication and connectivity of sensor nodes within the whole network area. In MEACBM, after the deployment of sensor nodes and formation of clusters, the whole network area is divided into sectors and inside each sector a mobile sensor node is placed which act as Mobile Data Collector (MDC) for collecting data from CHs. This technique helps in significantly reducing the energy consumption of sensor nodes for transferring information to the Base Station (BS). Simulation performance based results indicates the effectiveness of MEACBM routing protocols by comparing it with other contemporary cluster based routing protocols in terms of network lifetime, stability, throughput, number of CHs and number of dead nodes.

Energy Aware Cluster Based Multi-hop Energy Efficient Routing Protocol using Multiple Mobile Nodes (MEACBM) in Wireless Sensor Networks

Data collection is one of the main operations performed in Wireless Sensor Networks (WSNs). Even if several interesting approaches on data collection have been proposed during the last decade, it remains a research focus in full swing with a number of important challenges. Indeed, the continuous reduction in sensor size and cost, the variety of sensors available on the market, and the tremendous advances in wireless communication technology have potentially broadened the impact of WSNs. The range of application of WSNs now extends from health to the military field through home automation, environmental monitoring and tracking, as well as other areas of human activity. Moreover, the expansion of the Internet of Things (IoT) has resulted in an important amount of heterogeneous data that are produced at an exponential rate. Furthermore, these data are of interest to both industry and in research. This fact makes their collection and analysis imperative for many purposes. In view of the characteristics of these data, we believe that very large-scale and heterogeneous WSNs can be very useful for collecting and processing these Big Data. However, the scaling up of WSNs presents several challenges that are of interest in both network architecture to be proposed, and the design of data-routing protocols. This paper reviews the background and state of the art of Big Data collection in Large-Scale WSNs (LS-WSNs), compares and discusses on challenges of Big Data collection in LS-WSNs, and proposes possible directions for the future.

https://www.mdpi.com/1424-8220/18/12/4474/pdf

Big Data Collection in Large-Scale Wireless Sensor Networks.

Ontologies allow researchers, domain experts, and software agents to share a common understanding of the concepts and relationships of a domain. The past few years have seen the publication of ontologies for a large number of domains. The modeling and simulation community is beginning to see potential for using these ontologies in the modeling process. This paper presents a method for using the knowledge encoded in ontologies to facilitate the development of simulation models. It suggests a technique that establishes relationships between domain ontologies and a modeling ontology and then uses the relationships to instantiate a simulation model as ontology instances. Techniques for translating these instances into XML based markup languages and then into executable models for various software packages are also presented.

/pdf/from-domain-ontologies-to-modeling-ontologies-to-executable-4p5168deiu.pdf

From domain ontologies to modeling ontologies to executable simulation models

This paper presents a graph-coloring-based algorithm for the exam scheduling application, with the objective of achieving fairness, accuracy, and optimal exam time period. Through the work, we consider few assumptions and constraints, closely related to the general exam scheduling problem, and mainly driven from accumulated experience at various universities. The performance of the algorithm is also a major concern of this paper.

A New Exam Scheduling Algorithm Using Graph Coloring.

Using mobile sinks to collect information in wireless sensor networks is an interesting area of research. As a result, a variety of mobility models were proposed by researchers over the years where each mobility model has its own properties that may affect the performance of the network in a way that differs from other models entitled with different properties. In this paper we provide a survey of mobility models that can be used in wireless sensor networks since it is important to provide a classification of the available models. Therefore, several mobility models were reviewed in the proposed work. These models were classified into two main categories namely homogenous and heterogeneous mobility. The goal of the work proposed in this paper is to provide researchers with a clear idea about the available mobility models and their properties. Additionally, we aim to provide researchers with guidelines to help them choose mobility models properly.

http://cisjournal.org/journalofcomputing/archive/vol4no9/vol4no9_3.pdf

A Survey of Sink Mobility Models for Wireless Sensor Networks

The recent surge of popularity has established Mashups as an important category of Web 2.0 applications. Mashups are essentially Web services that are often created by end-users. They aggregate and manipulate data from sources around the World Wide Web. Surprisingly, there are very few studies on the scalability and performance of mashups. In this paper, we study caching as a vehicle for enhancing the scalability and the efficiency of mashups. Although caching has long been used to improve the performance of Web services, mashups pose some unique challenges that necessitate a more dynamic approach to caching. Towards this end, we present MACE - a cache specifically designed for mashups. In designing the MACE framework this paper makes three technical contributions. First, we present a model for representing mashups and analyzing their performance. Second, we propose an indexing scheme that enables efficient reuse of cached data for newly created mashups. Finally, this paper also describes a novel caching policy that analyzes the costs and benefits of caching data at various stages of different mashups and selectively stores data that is most effective in improving system scalability. We report experiments studying the performance of the MACE system.

/pdf/mace-a-dynamic-caching-framework-for-mashups-3lezdj73ip.pdf

MACE: A Dynamic Caching Framework for Mashups

Recently, overlay network-based collaborative applications such as instant messaging, content sharing, and Internet telephony are becoming increasingly popular. Many of these applications rely upon data-replication to achieve better performance, scalability, and reliability. However, replication entails various costs such as storage for holding replicas and communication overheads for ensuring replica consistency. While simple rule-of-thumb strategies are popular for managing the cost-benefit tradeoffs of replication, they cannot ensure optimal resource utilization. This paper explores a multi-objective optimization approach for replica management, which is unique in the sense that we view the various factors influencing replication decisions such as access latency, storage costs, and data availability as objectives, and not as constraints. This enables us to search for solutions that yield close to optimal values for these parameters. We propose two novel algorithms, namely multi-objective Evolutionary (MOE) algorithm and multi-objective Randomized Greedy (MORG) algorithm for deciding the number of replicas as well as their placement within the overlay. While MOE yields higher quality solutions, MORG is better in terms of computational efficiency. The paper reports a series of experiments that demonstrate the effectiveness of the proposed algorithms.

/pdf/replication-in-overlay-networks-a-multi-objective-220je57ebg.pdf

Osama Al-Haj Hassan

Papers

From domain ontologies to modeling ontologies to executable simulation models

A New Exam Scheduling Algorithm Using Graph Coloring.

A Survey of Sink Mobility Models for Wireless Sensor Networks

MACE: A Dynamic Caching Framework for Mashups

Replication in Overlay Networks: A Multi-objective Optimization Approach