Grid computing on mobile phones

Cloud computing is a collection of resources and services offered through the Internet. It is an Internet-based computing, where common resources, software and information are delivered to devices and computers on-demand. Common example of cloud services is Google apps, by Google and Microsoft SharePoint. Cloud computing is receiving a good deal of attention lately because of the implications for better flexibility and availability at very minor cost. Public cloud computing is one of the several deployment models. A public cloud is a cloud computing environment where infrastructure is available to the general public on the internet. Since cloud computing share distributed resources via the network in the open environment, security problems becomes more important to develop the secure cloud computing application. In this paper, we pay attention to the key security issues and challenges in public cloud computing environment which will aware both end users and vendors to get the information about the key security issues associated with cloud computing. We also discuss the precautions taken for mitigate the security issues.

Cloud computing and education sounds ambiguous on the face of it. Naturally, it's because, very few individuals, publishers and users alike come from the education sector. In most cases, cloud computing is only associated with businesses and how they can leverage their efficiencies. Just to introduce how the cloud deserves a place in our current education institution, it's important to reiterate the education philosophy. Its essence is knowledge. It's this knowledge which brings advancement, achievement and success. However, there are several things which make these parameters unattainable. In blunt language, this is failure. Small classrooms, lack or resources, short-handed staff, lack of adequate teachers…the list is endless. One way or the other, cloud computing can be utilized to improve education standards and activities. The end result will be to curb the above problems and instead, boost performance.

Grid computing has emerged from category of distributed and parallel computing where the heterogeneous resources from different network are used simultaneously to solve a particular problem that need huge amount of resources. Potential of Grid computing depends on my issues such as security of resources, heterogeneity of resources, fault tolerance & resource discovery and job scheduling. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing resources and is an NP-complete problem. To achieve the promising potential of grid computing, an effective and efficient job scheduling algorithm is proposed, which will optimized two important criteria to improve the performance of resources i.e. makespan time & resource utilization. With this, we have classified various tasks scheduling heuristic in grid on the basis of their characteristics.

org/ncwc/index Scope & Topics 8 th International Conference of Networks, Communications, Wireless and Mobile Computing (NCWC 2022) looks for significant contributions to the Computer Networks, Communications, wireless and mobile computing for wired and wireless networks in theoretical and practical aspects. Original papers are invited on computer Networks, network protocols and wireless networks, Data communication Technologies, network security and mobile computing. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science & Engineering.

• Distributed algorithms of mobile computing • OS and middleware support for mobile computing and networking • Routing, and communication primitives in ad-hoc and sensor networks • Synchronization and scheduling issues in mobile and ad hoc networks • Resource management in mobile, wireless and ad-hoc networks • Data management on mobile and wireless computing • Integration of wired and wireless networks • Broadband access networks • Energy saving protocols for ad hoc and sensor networks • Complexity analysis of algorithms for mobile environments • Information access in wireless networks • Algorithms and modeling for tracking and locating mobile users • Satellite communications • Cryptography, security and privacy of mobile & wireless networks

Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.

Service-oriented computing is a popular design methodology for large scale business computing systems. Grid computing enables the sharing of distributed computing and data resources such as processing, networking and storage capacity to create a cohesive resource environment for executing distributed applications in service-oriented computing. Grid computing represents more business-oriented orchestration of pretty homogeneous and powerful distributed computing resources to optimize the execution of time consuming process as well. Grid computing have received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational in e-Science and businesses. The objective of the journal is to serve as both the premier venue for presenting foremost research results in the area and as a forum for introducing and exploring new concepts. Authors are solicited to contribute to this Open Access peer-reviewed Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

We considered building high performance tools on the Raspberry Pi 4. We implemented OpenMP and OpenCoarrays Fortran in conjunction with the statistical language R. We found that the OpenCoarrays is more effective when working with vectors, while OpenMP is better in the arena with large matrices in a geostatistics application. These results can be very useful for researchers with limited access to high performance tools or limited funding.

Service-oriented computing is a popular design methodology for large scale business computing systems. Grid computing enables the sharing of distributed computing and data resources such as processing, networking and storage capacity to create a cohesive resource environment for executing distributed applications in service-oriented computing. Grid computing represents more business-oriented orchestration of pretty homogeneous and powerful distributed computing resources to optimize the execution of time consuming process as well. Grid computing have received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational in e-Science and businesses. The objective of the journal is to serve as both the premier venue for presenting foremost research results in the area and as a forum for introducing and exploring new concepts. Authors are solicited to contribute to this Open Access peer-reviewed Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

International Journal of Mobile ad hoc and sensor networks(IJMSN) is a open access journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Computer Networks & Communications.

Grid and peer-to-peer (P2P) networks are two ideal technologies for file sharing. A P2P grid is a special case of grid networks in which P2P communications are used for communication between nodes and trust management. Use of this technology allows creation of a network with greater distribution and scalability. Semantic grids have appeared as an expansion of grid networks in which rich resource metadata are revealed and clearly handled. In a semantic P2P grid, nodes are clustered into different groups based on the semantic similarities between their services. This paper proposes a reputation model for trust management in a semantic P2P Grid. We use fuzzy theory, in a trust overlay network named FR TRUST that models the network structure and the storage of reputation information. In fact we present a reputation collection and computation system for semantic P2P Grids. The system uses fuzzy theory to compute a peer trust level, which can be either: Low, Medium, or High. Our experimen...

India is an agriculture based developing country. Information dissemination to the knowledge intensive agriculture sector is upgraded by mobile-enabled information services and rapid growth of mobile telephony. It bridge the gap between the availability of agricultural input and delivery of agricultural outputs and agriculture infrastructure. Mobile computing, cloud computing, machine learning and soft computing are the immerging techniques which are being used in almost all fields of research. Apart from this, they are also useful in our day-today activities such as education, medical and agriculture. This paper explores how Android Apps of agricultural services have impacted the farmers in their farming activities.

This paper describes an architecture model for multiagent systems that was developed in the European project LEAP (Lightweight Extensible Agent Platform). Its main feature is a set of generic services that are implemented independently of the agents and can be installed into the agents by the application developer in a flexible way. Moreover, two applications using this architecture model are described that were also developed within the LEAP project. The application domain is the support of mobile, virtual teams for the German automobile club ADAC and for British Telecommunications.

In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in computation intensive situations data may be pulled to the jobs. This kind of scheduling, in which there ...

In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in computation intensive situations data may be pulled to the jobs. This kind of scheduling, in which there ...

In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in computation intensive situations data may be pulled to the jobs. This kind of scheduling, in which there ...

7th International conference on Advanced Computing (ADCOM 2021) will provide an excellent
international forum for sharing knowledge and results in theory, methodology and applications of
Computer Science, Engineering and Information Technology. The Conference focuses on all technical
and practical aspects of high performance computing, green computing, pervasive computing, cloud
computing etc.

• Distributed algorithms of mobile computing • OS and middleware support for mobile computing and networking • Routing, and communication primitives in ad-hoc and sensor networks • Synchronization and scheduling issues in mobile and ad hoc networks • Resource management in mobile, wireless and ad-hoc networks • Data management on mobile and wireless computing • Integration of wired and wireless networks • Broadband access networks • Energy saving protocols for ad hoc and sensor networks • Complexity analysis of algorithms for mobile environments • Information access in wireless networks • Algorithms and modeling for tracking and locating mobile users • Satellite communications • Cryptography, security and privacy of mobile & wireless networks

Stochastic Petri Net (SPN) is a tool by which validation of discrete-event systems are studied and modeled. SPN Theory allows systems to model as mathematical models. A Petri net is a graphical model useful for modeling systems exhibiting concurrent, asynchronous or nondeterministic behavior. The nodes of a Petri net are places (drawn as circles), representing conditions, and transitions (drawn as bars), representing events. Tokens (drawn as small filled circles) are moved from place to place when the transitions, when we Trace Stochastically and randomly on PN models called it Stochastic Petri net (SPN) model. We conclude benifit information from dynamic beheviour and structured of system modeled with stochastic petri net analysis, hence, this information could use for evaluating, some guess for make, modify systems. SPN use extendly for system analysis. one of the problems in SPN are in adaptive thems.therefore, SPN are unable to reach prev information .if each transaction enable each time then each of them could selected for next firing.this feathres reminding the facts that if this event accure and the eccuring is not conccurrncy each firing can takeplace and event accuring not changend during the time and this is against dynamic and real world, hence, simulation is like main program. The goal is that the simulated model was used for analysis of system perfomance.thus, the problems and lack position of simulated model is appeared. But, SPN tools can not lonely resolve and modify this problems and it can not predict next optimale state. In this thesis, our main goal is making a adaptive stochastic petri net model based on learning automata and its usage in resource allocation in econimic and computing grids.. Adaptive Stochastic Petri nets based on learning automata predicts the following optimized state through getting information from former system states and dynamic environmental reactions, makes the system current states appeared based on that, changes the probability of events  occurrences during the time and causes the events to be activated based on probability of occurrence. Updating system state can several major help in learning and educating petri net. Here, petri net adapting in several applications considered. We use SPNP simulation tool for simulating SPN. In another part of this thesis we used prposed method in ASPN in resource allocation in grid computing. We have proposed a new method to optimize the resource Scheduling in grid computing based on categorized requests in three layers which depend on Hierarchical Stochastic Petri net model called HSPN. These layers are Home, Local and Grid layers. We have divided our tasks in these layers. Each layer has special function to receive subtask and deliver data to up/down layer. Then, we have compare HSPN with other resource scheduling such as Min.min and Max.min algorithms. In second part of thesis we considered resource allocation in econimical grid based on learning automata in diffrent states. For this reason, we considerd time measurement for adaptive model for resource allocation in econimical grid. Here, we considered independent allocated tasks to resources as at-onec and phased, an idea based on learning automata and based on related works that Mr Bouyya and mahdavifar compared. ALATO is proposed algorithms based on Learning Automata.

The growing availability of networked mobile devices has created a vast collective pool of unexploited computing resources. In this paper we analyze the challenges for harvesting this potential for grid computing. The inherent limitations of typical mobile devices, such as reduced CPU performance, small secondary storage, heightened battery consumption sensitivity, and unreliable low-bandwidth communication are outraced by number of smart-phones sold annually, suggesting that the concept should not be prematurely dismissed. Given the enormous benefits of mobile grid computing, solutions to compensate for the inherent limitations of these devices must be developed in order to successfully utilize them in the Grid.

While inclusion of mobile devices into grid computing provides numerous advantages, the current implementations are either too complex or too specific, hence, cannot often be used efficiently by small to medium scale organizations. Further, diversity of platforms & development environments and virtual non-existence of high-end mobile devices until last few years were some of the hindrances in the path of incorporating mobile devices in real world grids. To address these lacunae, herein we introduce a new simplistic framework “jUniGrid” for integrating mobile devices as workstations in heterogeneous grid computing (desktop volunteer grid computing systems, DGVCS) to be used for performing high complexity computational problems. jUniGrid is a flexible grid architecture designed to deploy java-enabled devices (mobile or otherwise) as grid-nodes.

The resource allocation in Grid computing system needs to be scalable, reliable and smart. It should also be adaptable to change its allocation mechanism depending upon the environment and user's requirements. Therefore, a scalable and optimized approach for resource allocation where the system can adapt itself to the changing environment and the fluctuating resources is essentially needed. In this paper, a Teaching Learning based optimization approach for resource allocation in Computational Grids is proposed. The proposed algorithm is found to outperform the existing ones in terms of execution time and cost. The algorithm is simulated using GRIDSIM and the simulation results are presented.

The predominant grid authentication mechanisms use public key infrastructure (PKI). Nonetheless, certificate-less public key cryptography (CL-PKC) has several advantages that seem to well align with the demands of grid computing. Security and efficiency are the main objectives of grid authentication protocols. Unfortunately, certificate-less authenticated key agreement protocols rely on the bilinear pairing, that is extremely computational expensive. In this paper, we analyze the recently secure certificate-less key agreement protocols without pairing. We then propose a novel grid pairing-free certificate-less two-party authenticated key agreement (GPC-AKA) protocol, providing a more lightweight key management approach for grid users. We also show, a GPC-AKA security protocol proof using formal automated security analysis Sycther tool.

Grid computing enlarge with computing platform which is collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organization to form a distributed high performance computing infrastructure. Grid computing solves the complex computing problems amongst multiple machines. Grid computing solves the large scale computational demands in a high performance computing environment. The main emphasis in the grid computing is given to the resource management and the job scheduler .The goal of the job scheduler is to maximize the resource utilization and minimize the processing time of the jobs. Existing approaches of Grid scheduling doesn't give much emphasis on the performance of a Grid scheduler in processing time parameter. Schedulers allocate resources to the jobs to be executed using the First come First serve algorithm. In this paper, we have provided an optimize algorithm to queue of the scheduler using various scheduling methods like Shortest Job First, First in First out, Round robin. The job scheduling system is responsible to select best suitable machines in a grid for user jobs. The management and scheduling system generates job schedules for each machine in the grid by taking static restrictions and dynamic parameters of jobs and machines into consideration. The main purpose of this paper is to develop an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs. Queues can be optimized by using various scheduling algorithms depending upon the performance criteria to be improved e.g. response time, throughput. The work has been done in MATLAB using the parallel computing toolbox.

Grid computing is a type of distributed computing which allows sharing of computer resources through Internet. It not only allows us to share files but also most of the software and hardware resources. An efficient resource discovery mechanism is the fundamental requirements for grid computing systems, as it supports resource management and scheduling of applications. Among various discovery mechanisms, Peer-to-Peer (P2P) technology witnessed rapid development and the key component for this success is efficient lookup applications of P2P. Chord is a P2P structural model widely used as a routing protocol to find resources in grid environment. Plenty of ideas are implemented by researchers to improve the lookup performance of chord protocol in Grid environment. In this paper, we discuss the recent researches made on Chord Structured P2P protocol and present our proposed methods in which we use the address of Recently Visited Node (RVN) and fuzzy technique to locate the grid resources to reduce message and time complexity.

In the recent years, service-based approaches for sharing of data among repositories and online learning are rising to prominence because of their potential to meet the requirements in the area of high performance computing. Developing education based grid services and assuring high availability, reliability and scalability are demanding in web service architectures. On the other hand, grid computing provides flexibility towards aggregating distributed CPU, memory, storage, data and supports large number of distributed resource sharing to provide the full potential for education like applications to share the knowledge that can be attainable on any single system. However, the literature shows that the potential of grid resources for educational purposes is not being utilized yet. In this paper, an education based grid framework architecture that provides promising platform to support sharing of geographically dispersed learning content among universities is developed. It allows students, faculty and researchers to share and gain knowledge in their area of interest by using e-learning, searching and distributed repository services among universities from anywhere, anytime. Globus toolkit 5.2.5 (GTK) software is used as grid middleware that provides resource access, discovery and management, data movement, security, and so forth. Furthermore, this work uses the OGSA-DAI that provides database access and operations. The resulting infrastructure enables users to discover education services and interact with them using the grid portal.

We address the problem of deciding when to spin down the disk of a mobile computer in order to extend battery life. Since one of the most critical resources in mobile computing environments is battery life, good energy conservation methods can dramatically increase the utility of mobile systems. We use a simple and efcient algorithm based on machine learning techniques that has excellent performance in practice. Our experimental results are based on traces collected from HP C2474s disks. Using this data, the algorithm outperforms several algorithms that are theoretically optimal in under various worst-case assumptions, as well as the best xed time-out strategy. In particular, the algorithm reduces the power consumption of the disk to about half (depending on the disk's properties) of the energy consumed by a one minute xed time-out. Since the algorithm adapts to usage patterns, it uses as little as 88% of the energy consumed by the best xed time-out computed in retrospect.

We address the problem of deciding when to spin down the disk of a mobile computer in order to extend battery life. Since one of the most critical resources in mobile computing environments is battery life, good energy conservation methods can dramatically increase the utility of mobile systems. We use a simple and efficient algorithm based on machine learning techniques that has excellent performance in practice. Our experimental results are based on traces collected from HP C2474s disks. Using this data, the algorithm outperforms several algorithms that are theoretically optimal in under various worst-case assumptions, as well as the best fixed time-out strategy. In particular, the algorithm reduces the power consumption of the disk to about half (depending on the disk's properties) of the energy consumed by a one minute fixed time-out. Since the algorithm adapts to usage patterns, it uses as little as 88% of the energy consumed by the best fixed time-out computed in retrospect.

Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.

International journal of Mobile Network Communications & Telematics (IJMNCT) is an open access peer-reviewed journal that addresses the impacts and challenges of mobile communications and telematics. The journal also aims to focus on various areas such as ecommerce, e-governance, telematics, tele learning nomadic computing, data management, related software and hardware technologies, and mobile user services. The journal documents practical and theoretical results which make a fundamental contribution for the development of mobile communication technologies.

Grid and peer-to-peer (P2P) networks are two ideal technologies for file sharing. A P2P grid is a special case of grid networks in which P2P communications are used for communication between nodes and trust management. Use of this technology allows creation of a network with greater distribution and scalability. Semantic grids have appeared as an expansion of grid networks in which rich resource metadata are revealed and clearly handled. In a semantic P2P grid, nodes are clustered into different groups based on the semantic similarities between their services. This paper proposes a reputation model for trust management in a semantic P2P Grid. We use fuzzy theory, in a trust overlay network named FR TRUST that models the network structure and the storage of reputation information. In fact we present a reputation collection and computation system for semantic P2P Grids. The system uses fuzzy theory to compute a peer trust level, which can be either: Low, Medium, or High. Our experimental results demonstrate that FR TRUST combines low (and therefore desirable) a good computational complexity with high ranking accuracy.

Grid and peer-to-peer (P2P) networks are two ideal technologies for file sharing. A P2P grid is a special case of grid networks in which P2P communications are used for communication between nodes and trust management. Use of this technology allows creation of a network with greater distribution and scalability. Semantic grids have appeared as an expansion of grid networks in which rich resource metadata are revealed and clearly handled. In a semantic P2P grid, nodes are clustered into different groups based on the semantic similarities between their services. This paper proposes a reputation model for trust management in a semantic P2P Grid. We use fuzzy theory, in a trust overlay network named FR TRUST that models the network structure and the storage of reputation information. In fact we present a reputation collection and computation system for semantic P2P Grids. The system uses fuzzy theory to compute a peer trust level, which can be either: Low, Medium, or High. Our experimen...

Mobile Grid (MG) is emerging as a new computing paradigm due to advancement in mobile computing and communication technologies. MG provides an ecosystem to execute a computational intensive tasks which is divided into several subtasks. Each subtask is allocated for execution to an available and capable mobile devices for computation and finally collect results from each mobile user based on requirements of a task and a node is identified for computation. Taking into consideration its mobility, processing power, storage and battery life. Key issues that need to be addressed, are mobility of users, limited battery life of mobile devices and their failure handling during computation. Our proposed system will provide resource allocation scheme addressing the key issues described above.

Service-oriented computing is a popular design methodology for large scale business computing systems. Grid computing enables the sharing of distributed computing and data resources such as processing, networking and storage capacity to create a cohesive resource environment for executing distributed applications in service-oriented computing. Grid computing represents more business-oriented orchestration of pretty homogeneous and powerful distributed computing resources to optimize the execution of time consuming process as well. Grid computing have received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational in e-Science and businesses. The objective of the journal is to serve as both the premier venue for presenting foremost research results in the area and as a forum for introducing and exploring new concepts. Authors are solicited to contribute to this Open Access peer-reviewed Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

Advanced Computing: An International Journal (ACIJ) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced computing. The journal focuses on all technical and practical aspects of high performance computing, green computing, pervasive computing, cloud computing etc. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in computing and establishing new collaborations in these areas.

Service-oriented computing is a popular design methodology for large scale business computing systems. Grid computing enables the sharing of distributed computing and data resources such as processing, networking and storage capacity to create a cohesive resource environment for executing distributed applications in service-oriented computing. Grid computing represents more business-oriented orchestration of pretty homogeneous and powerful distributed computing resources to optimize the execution of time consuming process as well. Grid computing have received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational in e-Science and businesses. The objective of the journal is to serve as both the premier venue for presenting foremost research results in the area and as a forum for introducing and exploring new concepts. Authors are solicited to contribute to this Open Access peer-reviewed Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

12 th International Conference on Grid Computing (GridCom 2020) Service-oriented computing is a popular design methodology for large scale business computing systems. Grid computing enables the sharing of distributed computing and data resources such as processing, networking and storage capacity to create a cohesive resource environment for executing distributed applications in service-oriented computing. Grid computing represents more business-oriented orchestration of pretty homogeneous and powerful distributed computing resources to optimize the execution of time consuming process as well. Grid computing have received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational in e-Science and businesses. The objective of the meeting is to serve as both the premier venue for presenting foremost research results in the area and as a forum for introducing and exploring new concepts.

International Journal of Wireless & Mobile Networks (IJWMN) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Wireless & Mobile Networks. The journal focuses on all technical and practical aspects of Wireless & Mobile Networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced wireless & mobile networking concepts and establishing new collaborations in these areas.

Load balancing functionalities are crucial for best Grid performance and utilization. Accordingly,this paper presents a new meta-scheduling method called TunSys. It is inspired from the natural phenomenon of heat propagation and thermal equilibrium. TunSys is based on a Grid polyhedron model with a spherical like structure used to ensure load balancing through a local neighborhood propagation strategy. Furthermore, experimental results compared to FCFS, DGA and HGA show encouraging results in terms of system performance and scalability and in terms of load balancing efficiency.