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Smart community setups nowadays are subjected to complicated issues such as instability, intermittent integration of the load at the demand side, and lack of intelligent two-way communication process. These issues need to be addressed in terms of a balanced power demand dispatch (DD) in the real-time or day-ahead duplex signal regime under multi-microgrids. This paper offers an intelligent multi-agent-based approach that works between different levels of communication and their respective layers for a community-based system to optimize the power in community-based multi-microgrids model. This will further enhance user personal comfort. Constraints relative to cost minimization also have a relation with this model. A three-level structure with various layers of autonomous agents take intelligent decisions based on prioritized particle swarm optimization (P-PSO), prioritized plug and play (PPnP), and knapsack; considering DD as the main driver of the system to address objectives like price and power consumption uncertainties. Distinct smart home models, depending upon their living habits, are keenly observed providing their power infrastructure and personal comfort. Load appliances considered as load agents are individually contemplated for maximum proficiency. Furthermore, two-way communication between utility and consumers lowers down the risk of the inefficiency of the system.

Big data analytics has simplified processing complexity of large dataset in a distributed environment. Many state-of-the-art platforms i.e. smart grid has adopted the processing structure of big data and manages a large volume of data through MapReduce paradigm at distribution ends. Thus, whenever a wireless IoT edge node bundles a sensor dataset into storage media, MapReduce agent performs analytics and generates output into the grid repository. This practice has efficiently reduced the consumption of resources in such a giant network and strengthens other components of the smart grid to perform data analytics through aggregate programming. However, it consumes an operational latency of accessing large dataset from a central repository. As we know that, smart grid processes I/O operations of multi-homing networks, therefore, it accesses large datasets for processing MapReduce jobs at wireless IoT edge nodes. As a result, aggregate MapReduce at wireless IoT edge node produces a network congestion and operational latency problem. To overcome this issue, we propose Wireless IoT Edge-enabled Block Replica Strategy (WIEBRS), that stores in-place, partition-based and multi-homing block replica to respective edge nodes. This reduces the delay latency of accessing datasets for aggregate MapReduce and increases the performance of the job in the smart grid. The simulation results show that WIEBRS effective decreases operational latency with an increment of aggregate MapReduce job performance in the smart grid.

© 2019 Global IT Research Institute (GIRI). Apache Spark is known for its robustness in processing large-scale datasets in a distributed computing environment. This form of efficiency is highly observing because of the direct use of Random-Access Memory (RAM) in processing its resilient distributed datasets across the ecosystem. Recently, it is observed that, the memory utilization in computing spark jobs is mainly dependent on job containers, which are closely associated to persistent storage media components. Thus, spark jobs processing relevancy is tightly coupled to the type of storage container and in case of any dynamic resource allocation, the job loses its ratio of resource computation in existing container and increases a functional issue of processing large-scale datasets in spark ecosystem. In this paper, we propose dynamic container-based resource management framework, that shifts coupled associations of job profiles to dynamically available resource containers. Also, it relieves static container allocations and presumes them as a fresh piece of resource allocation for new job profile. The experimental evaluation shows that the proposed dynamic framework reduces wastage of resource allocations and increase ecosystem performance than default job profile in spark ecosystem.

Wireless sensor networks need middleware system for efficiently managing the constrained resource and sensing data because they need different sensing data type and protocol to communicate with heterogeneous sensor networks. Thus this paper proposes data-centric sensor middleware for heterogeneous sensor networks. The proposed middleware have to support various query processing of user applications, high-level request of users, manage heterogeneous sensor systems and universal sensing data type for node and user application.

Wireless sensor network (WSN) is formed by hundreds to thousands of nodes that communicate with each other updates information from time to time by passing data from one to another. This work aims to simultaneously improve the fidelity for high-integrity applications and decrease the end-to-end delay for delay-sensitive ones, even when the network is congested. To effective queue management, a queue scheduler allocates network resources by selecting a packet in the classified queue to access a single physical link with fixed capacity. We propose a dynamic queue management approach using fuzzy logic to quality of service (QoS) requirement in data integrity and delay differentiated routing (IDDR). The simulation results demonstrate that the proposed approach significantly reduces average end-to-end delay and increases packet deliver ratio and throughput compared to the existing routing algorithm.

The next generation smart grids aim at revolutionizing the traditional grid by introducing new features, concepts and services. One of these new features is the ability to connect a small-scale generation unit directly on the distribution network. This kind of power generation has been referred to as Distributed Generation (DG). This paper looks at a variety of issues concerning the integration of DG units with the smart grid. This paper indicates the benefits provided by this integration and highlights important design issues that are highly relevant. It also examines the services that are essential for effective DG integration.

Wireless sensor networks require energy-efficient data transmission because the sensor nodes have limited power. A cluster-based routing method is more energy-efficient than a flat routing method as it can only send specific data for user requirements and aggregate similar data by dividing a network into a local cluster. However, previous clustering algorithms have some problems in that the transmission radius of sensor nodes is not realistic and multi-hop based communication is not used both inside and outside local clusters. As energy consumption based on clustering is dependent on the number of clusters, we need to know how many clusters are best. Thus, we propose an optimal number of cluster-heads based on multi-hop routing in wireless sensor networks. We observe that a local cluster made by a cluster-head influences the energy consumption of sensor nodes. We determined an equation for the number of packets to send and relay, and calculated the energy consumption of sensor networks using it. Through the process of calculating the energy consumption, we can obtain the optimal number of cluster-heads in wireless sensor networks.

Wireless sensor networks (WSNs) are composed of many homogeneous or heterogeneous sensor nodes with limited resources. A sensor node is comprised of three components: a sensor, a processor and a wireless communication device. A sensor of nodes detect a change in surroundings, a processor processes sensing data collected from neighbour nodes or own environmental information, and a wireless communication device is capable to send and receive sensing data. Sensor networks consist of a great number of sensor nodes and one or several sink nodes. The role of a sensor node is to detect and process own environmental information, to convert it to sensing data, to send it to neighbour nodes or sink nodes, and to collect it from neighbour nodes. On the other hands, the role of a sink node is to collect sensing data from sensor nodes and to be gateway that interconnects different network and transmits data to it. Generally, sensor nodes of WSNs are randomly scattered on specific area for satisfying user’s requirements (detecting, observing and monitoring environment) and have to selforganized network. It is difficult to exchange and charge node battery as the area where sensor nodes are located in is inaccessible location. So, it is important issue to design powerefficient protocol method for low-power operation and prolonging the network lifetime (Akyildiz et al, 2002). A sensor node needs wireless ad-hoc network capability to collect sensing data of wireless sensor network without a communication infrastructure. Sensor networks are, however, not suitable for the existing ad-hoc routing method (Tubaishat & Madria, 2003) because of sensor nodes with limited capability. Thus sensor networks require wireless ad-hoc routing method considering self-organization, restrictive power, and data-based communication(Sohrabi et al, 2000) and need multi-hop routing mechanism because of the limited transmission radius of a sensor nodes. WSNs should design for routing algorithm considering low-power operation because it has limited features and is a traditional wireless networks completely different from ‘the network(Al-Karaki & A.E. Kamal, 2004). In WSNs, routing methods can divide into two routing mechanisms: ‘flat-routing’ and ‘hierarchical-routing’. The ‘flat-routing’ technique regards the whole network as one region, enabling all nodes to participate in one region. On 10

For network life time, load balancing and scalability, wireless sensor networks have to configure the network based on local management. Clustering algorithm is for satisfying above requirements. A cluster head selection of this algorithm requires to solve additional communication cost and unequal clustering compared with previous clustering algorithm. So, this paper proposes novel cluster head selection algorithm revised previous clustering algorithm.

The goal of wireless sensor networks is to collect sensing data on a specific region using wireless communication. The sink node gathers all local sensing data, processes them, and transmits them to users who use sensor networks. Generally, sensor nodes are low-cost, low power devices with limited sensing, computation and wireless communication capabilities. A sensor network applies to multi-hop communication on a large-scale network. As neighboring sensor nodes have similar data, clustering is an effective technique for ‘data-aggregation’. In the multi-hop based cluster formation technique, it is necessary that the number of cluster member nodes should be distributed equally due to the balance of cluster formation. Therefore, this paper proposes a method of cluster head selection to form equal cluster sizes in wireless sensor networks

Multi-agent system and OSGi technologies are essential elements in realizing the upcoming ubiquitous environments. Up until now, different approaches are proposed to support the reliability of multi-agent system level by many researchers. Also, there are mainly focus on fault-tolerance of detection/recovery in the inside system fault or each agent level. We have view on them; will be provide an effective solution of service level for supporting the service reliability of an extended Directory Facilitator (DF) in multi-OSGi agent system. We propose a new, more reliable and extendable DF architecture, and present a detection/recovery algorithm of service fault for safety in railroad system. Through the proposed fault-tolerance architecture, the extended DF of multi-OSGi agent system can improve reliability and interoperability of the service level.

WSNs middleware is software positioned between applications and the operating system in sensor nodes. This middleware should have a communication function between the sensor nodes, to support good interactive functions between the user's applications. It must balance the resource use between the client and server system. WSNs comprise server-side middleware and in-network middleware. Server-side middleware supports application services efficiently in the server system. In-network middleware, located between sensor nodes, is in charge of managing the inner sensing information. We choose an event-driven network, the publish and subscribe network model, to support WSN. Using this model, sensor networks could reduce unnecessary energy consumption and respond to a variety of user requests.

The feature of 6LoWPAN is the capability of the dynamic assignment of 16bit short addresses. By using this dynamically assigned short address, a hierarchical routing is employed. In case of node failure, this hierarchical routing does not support a technique for path recovery. So, this paper proposes the path recovery technique for hierarchical routing over 6LoWPAN.

WSNs middle-ware is called software that is between applications and operating system in sensor node. Generally, to support good interaction functions between user's applications, this middleware should have a communication function between sensor nodes and have parts of balancing its resources between client and server's networks performance sides. For this reason, WSNs are composed by server-sides middleware and in-network middleware. The former, Server-side middleware is middleware to support application services efficiently in server system and the other, In-network middleware, located between sensor nodes, is in charge of managing inner sensing information. Therefore, we choose publish and subscribe network model, one of event-driven network methods, to support WSNs better than other ones. By using this model, sensor networks could reduce unnecessary energy cost and response to users' variety requests.

The agent systems can register, deregister and search the information of agent and services. Amount of the agent systems and the information according to agent and service are existed. The differences of the information specification make not easy to the relevancy about them. Thus, we propose the agent service system (ASS) to find the relevancy among the agents information and to manage them. The ASS can provide the various services to the other multi-agent systems or general systems that may be not the agent platform.

Mobile agent is important in mobile agent based distributed environment. The mobile agent performs a purpose through accesses to resources of the remote host by migrating from one host to another host or interactions between agents. Therefore communications between the mobile agents is important. However, there are communication failures problem and message forwarding errors due to the mobile agent's properties. Hence, communication protocol requires location-transparency, reliability, high-efficiency, asynchrony and self-adaptability and there are mechanisms to satisfy the requirements. In this paper, we propose mobile agent communication mechanism using Home Server and Sub Server. By using the mechanism, we can provide reliable message delivery services that solve the problems in the previous methods for communication failures and message forwarding.

Service discovery in ubiquitous environments faces various issues such as dynamic-topology, devices-capability, resource-sharing, interoperability etc. In this paper, we propose Service Discovery Middleware (SDM) to solve the interoperability issue by using Discovery Middleware (DM), which was introduced by the FIPA (Foundation for Intelligent Physical Agents) [1]. The SDM provides an appropriate choice for providing interoperability in heterogeneous environments. Moreover, it supports a means for autonomic discovery of heterogeneous integration services in ubiquitous computing and transparency between users and services. With these ideas in mind, we design a simple mechanism for building a wide range of distributed services and applications as well as for supporting a softness and adaptable means to control and manage the Service Discovery Protocols (SDP). Furthermore, we implement as an example, a Personal Agent (PA) platform based on the FIPA-OS agent platform, in order to provide SDM component functionality [10] [20].

The traditional server-centric design for P2P service discovery is not suitable for ad-hoc environments. In this paper, in order to facilitate the inter operation of ad-hoc environments with other platforms, we introduce D/sup 2/HT, an algorithm which enables directory federation using DHT, in order to support open scalability. We also introduce the lightweight service discovery (LSD) protocol based on the FIPA compatible agent framework. Our approach overcomes the reconfiguration problems associated with other DHT variants (e.g. Chord (Stoica et al., 2001), CAN (Ratnasamy, 2001) and Pastry (Rowstron and Druschel, 2001), which arise when peers join/leave the network, as well as taking into consideration device limitations. We also present an initial implementation of LSD using iPAQs and the D/sup 2/HT-enabled FIPA agent platform.

The Simple Object Access Protocol (SOAP) is a novel protocol which supports information exchange in a decentralized, distributed environment, which brings flexibility and extensibility to the communication and invocations among remote hosts. However, SOAP requires a high performance for collaboration such as service delivery and invocation. Furthermore, SOAP itself is not well suitable for mobile devices due to network bandwidth or resource-constraints problems. In this paper, we describe SOAP-based remote data access scheme which is comprised of XML and RPC technology. Especially, we focus on the scheme which is optimal over service discovery and invocation based on SOAP technology. Also, we apply the proposed scheme to LSD (Lightweight Service Discovery) which is a peer-to-peer, cache-based service discovery protocol for ad hoc environments.

Service discovery protocol is the main element that determines the efficiency in middleware platform of ubiquitous networks. Recently, a large number of middlewares supporting scalability which focus on the distributed computing and data sharing among tremendous peers has been proposed. However, due to the distributed nature of ad-hoc networks, peers may not be able to find other peers and corresponding resources persistently. Furthermore, current service discovery engines do not provide open scalability that can make them to interoperate with each other. In this paper, we propose a simple mechanism, which provides cross-platform interoperability through directory federation combined with DHT mechanism to support open scalability and lightweight service discovery in ad-hoc network based on FIPA compatibility agent framework.

Traditional service discovery mechanisms propose efficient and fast searching schemes for service discovery. And their schemes do not consider interoperability among discovery protocols. In this paper, we design an agent platform (AP) modifying FIPA-OS (Foundation for Intelligent Physical Agents Open Source) based on FIPA specifications. FIPA (Foundation for Intelligent Physical Agents) is a nonprofit organization aimed at producing standards for the interoperation of heterogeneous software agents. Until now FIPA specifications have not been considering mobile ad hoc networks. In such environments, agents can 7 find services offered by other service discovery engines in heterogeneous networks. We can guarantee scalability, by adding DM (discovery middleware) modules in the AP. The DM helps agents find and use services exploiting existing service discoveries under ad hoc networks. We chose UPnP (universal plug and play) and LSD (lightweight service discovery protocol) as DMs among various service discovery technologies. UPnP is a set of protocols for service discovery under development by the UPnP forum and LSD is a new discovery protocol for mobile ad hoc networks emphasizing on cache management that we designed. On our AP, we can use the services which devices of UPnP and LSD provide.

In this paper, we propose SDRP: a new service discovery protocol combined with routing policies in MANETs. It performs the protocol acting upon a backbone and access network as well as any kind of distributed networks. We describe a service by a unique ID number and use a group-cast routing policy in advertising and requesting. In addition, the nodes in the reply path also cache the advertisement information. We compare SDRP with Flood and AODV in terms of overload, demand throughput and average delay. Simulation results show SDRP can save response time and accommodate even high mobility network environments

Service discovery middleware allows users to find and use services through service discovery protocols without previous knowledge of the locations or characteristics of the services with minimum manual efforts in heterogeneous and ubiquitous environments. For this reason, many researchers have carried out studies related to service discovery middleware and many papers dealing with this field have been published. However, when a number of service consumers request services from middle agents (e.g. matchmaker, broker, yellow page, blackboard, etc.) within the service discovery middleware, the middle agent does not guarantee efficient and rapid matching results because they only use a simple matching algorithm. In this paper, we address the issues of existing matching algorithms, and then propose a new matchmaking algorithm based on the marriage matching algorithm of ATM networks (Gusfield and Irving, 1989) to improve middle agents' performance, complementing shortcomings of existing matching algorithms. We also add priority based matching to the new algorithms. Through this priority, important service request messages are processed faster than request messages that have low priorities. We expect the proposed matchmaking mechanism to increase users' satisfaction in dynamic environments.

As the number of Internet services grows, it is becoming more important for the network users to be able to locate and utilize those services that are of interest to them. As a result, a service discovery protocols are coming to play an increasingly important role in highly dynamic networks. In this paper, we describe a new architecture for service discovery called LSD (Lightweight Service Discovery). The LSD is a peer-to-peer cache-based service discovery protocol for ad hoc environments. Through the LSD protocol, small handheld mobile devices with wireless connectivity can detect each other in their neighboring devices, and perceive whether particular shared services are available or not. In addition, the LSD solves the overhead problems which arise when traditional discovery protocols are applied to mobile ad hoc networks.

Service discovery is an important technology for ad hoc communications and collaboration in ubiquitous computing environments. However, such an environment will be vastly different from the traditional infrastructure-based environment. For this reason, we design a new discovery protocol for mobile ad hoc networks. LSD (Lightweight Service Discovery) is a peer-to-peer cache-based service discovery protocol for ad hoc environments. Through the LSD protocol, small handheld mobile devices with wireless connectivity can detect each other in their neighboring devices and also perceive that shared services are available or unavailable. Besides, LSD solves the overhead problems when traditional discovery protocols are applied to the mobile ad hoc networks. Finally, we show an implementation of LSD and do a tentative protocol test for our system using LG IBM Thinkpad and WinCE based iPAQ's

Service discovery middleware allows users to find and use services through service discovery protocols in heterogeneous and ubiquitous environments without previous knowledge of the specific service location or characteristics, and with minimum manual effort. For this reason, in recent years, a number of researchers have studied service discovery middleware and many of papers dealing with this field have been published. However, when a number of service consumers request services from middle agents (e.g. matchmaker, broker, yellow page, blackboard, lookup server, etc) within the service discovery middleware, the middle agents do not guarantee efficient and rapid matching results because they use only a simple matching algorithm based on set theory for match processing. In this paper we address issues of existing matching algorithms, and propose a new matchmaking method adopting the marriage matching algorithm of the ATM network [1] to improve middle agent performance, complementing shortcomings of the existing matching algorithms. Furthermore, we use traffic type (e.g. voice/video applications, data-sharing applications, convenience applications, and so on) priority information for providing application-oriented QoS.

In wireless local area networks, MAC protocol is the main element that determines the efficiency in sharing the bandwidth of the wireless channel. Recently lots of QoS supporting mechanisms which focus on the distributed MAC protocols of IEEE 802.11 were proposed. However, due to the distributed nature of ad hoc networks, nodes may not be able to schedule packets to guarantee QoS metrics. In this paper, we propose a simple mechanism, which reduces collision and delay between packets based on distributed fair scheduling (DFS). Simulation results show that the proposed algorithm outperforms the DFS from delay and throughput viewpoints.

The high speed network usually deals with two main issues. The first is fast switching to get good throughput. At present, the state-of-the-art switches are employing input queued architecture to get high throughput. The second is providing QoS guarantees for a wide range of applications. This is generally considered in output queued switches. For these two requirements, there have been lots of scheduling mechanisms to support both better throughput and QoS guarantees in high speed switching networks. In this paper, we present a scheduling algorithm for providing QoS guarantees and higher throughput in an input queued switch. The proposed algorithm, called Weighted Fair Matching (WFM), which provides QoS guarantees without output queues, i.e., WFM is a flow based algorithm that achieves asymptotically 100% throughput with no speed up while providing QoS.

Input-queued switch is useful for high bandwidth switches and routers because of lower complexity and fewer circuits than output-queued switch. However, it suffers HOL-blocking, which limits the throughput to 58%. To overcome HOL-blocking problem, many input-queued switches are controlled by sophisticated scheduling algorithms at centralized schedulers which restrict the design of the switch architecture. In this paper, we propose a simple scheduler called Pipelined and Prioritized Round Robin(PPRR) which is intrinsically distributed by each input-port. An iterative prioritized round robin scheduling algorithm in a pipelined fashion is provided. The proposed algorithm has less complexity and yet comparable performance with respect to other algorithms such as iSLIP and RPA. The effectiveness of PPRR is demonstrated with simulations under uniform and bursty traffic conditions.