Multi-agent management strategies rely either on the classic client-server architecture or complex inter-agent communications. Distributed control algorithms allow you to balance the load. In this paper, an innovative technology for organizing a distributed structure of servers is considered in such a way as to reduce the computational load on the nearest servers while maintaining an adequate response time to client requests, regardless of the geographical location of both clients and servers in the network. The proposed model allows to reduce the impact of random interference on short-term tasks in the system and decrease the summary duration of all long-term tasks, improving the quality of the augmented reality service provided in general.

In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically toward the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance.

In the paper a multi-agent network system of different computing nodes is considered. A problem of load balancing in the network is addressed. The problem is formulated as consensus achievement problem and solved via local voting protocol. Agents exchange information about their states in presence of noise in communication channels. At certain moment network system topology changes and new step size of control protocol is chosen to meet new conditions. Step size adjustment is done by stochastic approximation type algorithm. Analytically obtained optimal step size values are given. Simulation example demonstrating step size adjustment is provided.

The multi-agent approach and technology for distributed scheduling, coordination and control of several UAV in group in order to perform joint tasks in real time was considered. The network-centric multi-agent system for real-time task scheduling for UAV's group was proposed. Two part of sheduling initial scheduling and dynamic rescheduling (task redistributed) were considered. For real-time task redistributed the randomized local voting protocol was used. The architecture of system consists of three basic subsystem. The approach to the organization of subsystems and agents within each subsystem interaction was described).

This paper is devoted to the approximate consensus problem for stochastic networks of nonlinear agents with switching topology, noisy, and delayed information about agent states. A local voting protocol with nonvanishing (e.g., constant) step size is examined under time-varying environments of agents. To analyze dynamics of the closed-loop system, the so-called method of averaged models is used. It allows us to reduce analysis complexity of the closed-loop stochastic system. We derive the upper bounds for mean square distance between states of the initial stochastic system and its approximate averaged model. These upper bounds are used to obtain conditions for approximate consensus achievement. An application of general theoretical results to the load balancing problem in stochastic dynamic networks with incomplete information about the current states of agents and with changing set of communication links is considered. The conditions to achieve the optimal level of load balancing are established. The performance of the system is evaluated both analytically and by simulation.

In this paper the multi-agent stochastic systems are considered under randomly switched agents communications topology and noisy information about the current states of neighbouring agents. We study the consensus problem for such systems when controls actions are formed by the local voting protocol (stochastic approximation type algorithm). This protocol is applied to the load balancing distributed computer system and to the system of Unnamed Aerial Vehicles (the UAVs system). Obtained results are important for the control properties analysis of production or logistic networks, multiprocessor or multicomputer networks, etc.