Holonic Organization Research Articles

HMLB: Holonic multi-agent approach for preventive controllers load-balancing in SDN-enabled smart grid

Smart grid networks present advantages like improving reliability, security, scalability, etc. However, designing an efficient communication infrastructure for smart grid networks is a great challenge. This is because of its dependency on proprietary protocols and specific vendors. Software-defined-enabled smart grid (SDN-SG) tackles this problem by incorporating diverse protocols and standards including open source platforms. One of the most important questions in Software-defined Networking (SDN) is the controller placement problem being NP-Hard in nature. Therefore, the predominant goal of this paper is to diminish the time complexity by modeling the controller placement problem based on the holonic multi-agent system. The hierarchical structure of a holonic organization improves the computational complexity through the divide and conquer mechanism. Such an idea also decreases the distributed controllers' synchronization overhead which is an issue in the realm of SDN. On the other hand, the proper functioning of the smart grid has a strict dependency on time-critical services. Accordingly, the controller placement is supposed to be a Quality of Service-aware (QoS-aware) one. Also, intermittent topology changes in the smart grid and the occasional joining and leaving of members result in an unsteady traffic pattern and dynamicity of controller load. This research is a pioneer in providing a QoS-aware and dynamic controller placement mechanism for SDN-SG. Experimental results certify the preponderance of the approach over similar ones concerning computational complexity, packet loss, controllers’ synchronization overhead, and also load-balancing overhead.

A new hierarchical multi group particle swarm optimization with different task allocations inspired by holonic multi agent systems

Nowadays expert systems have been used in different fields. They must be able to operate as quickly and efficiently as possible. So, they need optimization mechanism in their different parts and optimization is a critical part of almost all expert systems. Because of difficulties in real world problems, traditional optimization techniques commonly cannot solve them. Therefore, stochastic algorithms are used to do the optimization in expert systems. Particle swarm optimization (PSO) is one the most famous stochastic optimization algorithms. But this algorithm has some difficulties like losing diversity, premature convergence, trapping in local optimums and imbalance between exploration and exploitation. To overcome these drawbacks, inspired by holonic organization in multi agent systems, a new hierarchical multi group structure for PSO is presented in this paper. Considering the particles in PSO as simple agents, PSO is a kind of multi agent system. Existence of different facilities and organizations in multi agent systems and their great impact on performance encouraged us to use them. So, inspired by holonic multi agent systems, a new structure for PSO is presented. This work has been done for the first time in the literature. Meanwhile, to promote exploration and exploitation ability of proposed structure and create a suitable balance between them, different tasks are assigned to different groups of this structure. So, a holonic PSO with different task allocations (HPSO-DTA) is created. It provides the opportunity to employ all aspects for empowering PSO including parameter settings, neighborhood topologies and learning strategies to enhance the ability of it unlike other versions of PSO that use only one of these aspects to improve their solutions. This structure provides a lot of advantages for PSO. It is a new topological structure that improves the performance of PSO. It provides several leaders with efficient information to guide the particles in the search space. Also, it helps to control suitable information flow between groups and particles in order to preserve diversity and prevent from trapping in local optimums. Meanwhile, with assigning different tasks to different groups of proposed structure, an appropriate balance between exploration and exploitation is created to enhance the performance of the algorithm. In each group, based on its assigned task, particles use different parameters settings, different dynamic neighborhood topologies and different learning strategies which are proposed in this paper to enhance the performance of algorithm. A set of thirty four benchmark functions are used to evaluate the performance of proposed structure. Proposed algorithm is compared with a set of well-known PSO algorithms that their efficiency have been proved. Experimental results and comparative analysis demonstrate good performance of HPSO-DTA compared to other algorithms. Its solution accuracy, convergence speed and robustness is completely appropriate especially in more complicated benchmarks.

Overload management with regard to fairness in session initiation protocol networks by holonic multiagent systems

SummarySession initiation protocol (SIP) is a widely used standard protocol for multimedia applications and IP multimedia subsystems. Internet protocol multimedia subsystem was introduced by the 3GGP signaling foundation as part of a set of next generation network architectures. Despite having useful practical features, SIP does not have suitable mechanisms to handle overload. This challenge creates a sharp drop in quality of service for next generation network users. Because a distributed SIP network is a complex system composed of subsystems interacting with one another, multiagent system is an appropriate method to model network interactions and to solve overload in SIP networks. In this paper, holonic organization is applied to reduce the multiagent system complexity in modeling a large SIP network. Holonic organization is a hierarchical structure in which each holon covers a geographical area of the SIP network at the first level. At the second level, upper‐level holons control the first‐level holons, and so on. Overload control is achieved by communication and the exchange of knowledge between the intelligent holons. Experimental results show that the proposed method prevents overload in the SIP network. The method also increases total throughput, reduces delay, and considers fairness in the SIP network.

The impact of diversity on performance of holonic multi-agent systems

There are Numerous researches in the fields of social sciences and multi-agent systems that are dedicated to studying the role of diversity vs. individual capabilities in design and performance of human and artificial societies. This paper addresses more complex multi-level structures, namely holarchies, in multi-agent systems, and conducts several analyses on the effect of individuals' behavioral diversities in the constitution and performance of the whole system. The hypothesis is that diversity directly affects the structure and performance of a holonic organization. In order to check this, we first proposed a diversity-based holonic model for multi-agent systems and then carried out a set of simulations in which a holonic multi-agent system is employed in a function optimization application. In these simulations, we manipulated the behavioral diversity of the agents in various ways and carefully observed the changes that occur on the effectiveness of the system. These observations include the quality of solutions, the height and composition of the constructed systems, and the time efficiency of the model. The empirical results show that as the diversity of intra-holon agents increases, the height of holarchy is reduced while the sizes of the holons tend to increase. On the other hand, this increase in diversity results in an increase in the performance of the system in situations that diversity of the initial population is high. However, when the diversity of the initial population is low, the diversities inside the holons need to be adjusted around 60 percent in order to boost the performance.

A dynamic distributed overload control mechanism in SIP networks with holonic multi-agent systems

Nowadays, session initiation protocol (SIP) is the most important application layer protocol for multi-media to create, modify, and terminate the sessions. SIP is the platform of next generation networks. In this way, SIP should be able to respond to the needs of such a largely-used network. One of the major problems in SIP networks is overload. The basic mechanism embedded in SIP cannot appropriately resolve the due problem by purely rejecting requests, which may cause collapse in network. Many methods have been proposed to overcome overload in SIP, among which, multi-agent systems are new agent-based and increasingly growing approaches. Multi-agent system is a powerful tool to model and develop the complex large scale distributed systems. In SIP network, each agent may point out to a server which is in interaction with the others. As a result, a distributed and complex system is simply modeled. The due complexity can be reduced by holonic organization. In this paper, SIP network is divided into geographical areas in which each holon controls an area. The entire network is controlled in hierarchical structure of holons. Holonics structure can be dynamically changed based on the circumstances parameters and the status of the network during execution. Holons implement an end-to-end window-based method. This method offers an appropriate window size for edge servers to control load from the beginning of the network and prevent network overload. The simulation results confirm improved throughput, as well as better reduced call setup delay, rapid response to change and fairness.

The control of myopic behavior in semi-heterarchical production systems: A holonic framework

Heterarchical control architectures are essentially founded on cooperation and full local autonomy, resulting in high reactivity, no master/slave relationships and local information retention. Consequently, these architectures experience myopic decision-making, bringing entities towards local optimality rather than the system’s overall performance. Although this issue has been identified as an important problem within heterarchical control architectures, it has not been formally studied. The aim of this paper is to identify the dimensions of myopic behavior and propose mechanisms to control this behavior. This study focuses on myopic behavior found in manufacturing control. For this particular study, we propose a holonic framework and a holonic organization that integrates specific mechanisms to control the temporal and social myopia. Our proposal was validated using simulations designed for solving the allocation problem in flexible manufacturing systems. These simulations were conducted to show the improvement by integrating the new mechanisms. These simulation results indicate that the myopic control mechanisms achieve better performance than the reactive strategies, because not only they introduce a planning horizon, but also because they balance local and global objectives, seeking a consensus.

Organizational design drivers to enable emergent creativity in web‐based communities

PurposeIn the stream of works studying complexity from an organizational viewpoint, literature is focused mainly on describing new organizational forms (holonic organization, circular organization, virtual corporation, …) and on conceptual works identifying new managerial principles to manage emergence (job enrichment, de‐regulation, …). But literature still lacks “actionable knowledge” on management of emergent processes. Therefore, the authors seek to propose an empirical analysis with the aim of finding the organizational design drivers that enable self‐organization. As creativity could be understood as an important precondition for both adaptation and innovation in an age of complexity, the authors focus on creativity emergence process.Design/methodology/approachThe analysis is based on a framework of self‐organization principles. The authors derived it from the literature and used it to empirically analyse open innovation web‐based platforms for creativity. They are deemed particularly important because their open and collaborative innovation process is often self‐organized and their collaboration relationships seem to be loosely coupled. Therefore, they are a good ground to investigate the alternatives to managerial hierarchy and the knowledge‐based organizations associated with emergence and self‐organization.FindingsThe results highlight important organizational design choices to enable self‐organization process: organic structure composed by activity systems to enable reconfiguration; roles enlargement and enrichment and cognitive diversity to enable redundancy; collaboration and participatory decision‐making and social capital and networking to enable interconnection; values adaptation, motivations and rules to enable sharing principle.Originality/valueThe paper contributes to the empirical knowledge on emergence process, translating the principles of self‐organization in managerial actions.

Modeling a holonic agent based solution by Petri nets

One of the key design issues for distributed systems is to find proper planning and coordination mechanisms when knowledge and decision capabilities are spread along the system. This contribution refers holonic manufacturing execution systems and highlights the way a proper modeling method - Petri nets - makes evident certain problems that can appear when agents have to simultaneously treat more goals. According to holonic organization the planning phase is mainly dependent on finding an appropriate resource allocation mechanism. The type of weakness is established by means of the proposed Petri net models and further proved by simulation experiments. A solution to make the holonic scheme avoid a failure in resource allocation is mentioned, too.

A hybrid algorithm based on particle swarm optimization and simulated annealing to holon task allocation for holonic manufacturing system

Manufacturing is currently undergoing a revolutionary transition with focus shifting from mass production to mass customization. This trend motivates a new generation of advanced manufacturing systems that can dynamically respond to customer orders and changing production environments. It is becoming increasingly important to develop control architectures that are reconfigurable and fault tolerant. A holonic manufacturing system (HMS) is a system of holons that can cooperate to achieve a common goal or objective. The holonic organization enables the construction of very complex systems that are efficient in the use of resources. This paper focuses on the dynamic re-configuration and task optimization of holonic manufacturing systems (HMS). The concept of dynamic virtual clustering is extended to the control process of a holarchy or holonic organization. A task-oriented clustering mechanism and a corresponding optimization algorithm are presented as an efficient approach to the holonic control in the HMS domain. The mediator-based dynamic virtual clustering mechanism is presented firstly. Then a negotiation strategy based on the contract net protocol is proposed for cooperative action among holons. Finally, a hybrid algorithm based on particle swarm optimization (PSO) and simulated annealing (SA) for holon task allocation is described to support the optimum organization of a holarchy. The hybrid algorithm combines the high speed of PSO with the powerful ability to avoid being trapped in local minimum of SA. Simulation results show that the proposed model and algorithm are effective.