Abstract
Self-organizing and self-adaptation are known as two necessary means for reducing costs and efforts required for the maintenance of complex software systems. In strong self-organizing systems, decision-making processes are distributed internally among system elements without any centralized control point (internal or external). In these systems, local communications of agents at the micro-level cause the emergent of macro-level behaviors, which can be seen from a global point of view. These global behaviors contain essential information that usually is ignored and is out of reach of agents. Via increasing context-awareness of agents, this information can be used by agents to improve the performance of the system. In this paper, inspired by the concept of consulting, a relation between the macro-level and micro-level is made. In summary, using information hidden in emergent behaviors, it is made an indirect and advice-based (non-compulsory) effect on agents at the micro-level. Therefore, first, the proposed self-advising property (as a property of the self-adaptive hierarchy) is defined. Then using the MAPE-K loop and stigmergic communication, the advising process is described. Besides, SASO-System is provided to describe the self-advising property and the advising process. This system is implemented on a case study of the NASA-ANTS mission. The comparison of results with other paper shows that using self-advising property reduces the time spent for self-protecting of leader agents in the scenario considered. Also, experimental results indicate that when the system is of self-advising property, the number of calls for the self-protecting function is reduced, and the decrease percentage of self-adaptive function calls is at the range of 1.86–13.56. Results also show that in 80% of radio ranges, the context-awareness of the self-advising system is better than or equal to the context-awareness of the non-self-advising system.
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