Implementation and evaluation of a self‐organizing artificial hormone system to assign time‐dependent tasks

Pacher, Mathias; Brinkschulte, Uwe

doi:10.1002/cpe.1815

Cited by 7 publications

(2 citation statements)

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“…The AHS provides self‐X properties, where X stands for configuration, optimization, and healing, respectively. Much effort was spent to improve the AHS's real‐time capabilities and to deal with time‐dependent tasks . We also evaluated strategies to secure the AHS against malicious attacks within an open network in .…”

Section: Related Workmentioning

confidence: 99%

Two‐level extensions of an artificial hormone system

Pacher

2015

Concurrency and Computation

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Summary The ARTIFICIAL HORMONE SYSTEM (AHS) is a decentralized software that is able to allocate tasks in a system of heterogeneous processing elements (PEs). Tasks are allocated according to their suitability for the heterogeneous PEs, the current PE load, and task relationships. The AHS also provides properties like self‐configuration, self‐optimization, and self‐healing in the context of task allocation. In addition, it is able to guarantee real‐time bounds for such self‐X properties. However, using self‐organization principles introduces increased system complexity such as control of system parameters for self‐organization and additional communication effort. In this contribution, we address these problems by using two different two‐level extensions of the AHS: we consider the choice and control of hormone parameters by an observer/controller architecture as first extension of the AHS and a HIERARCHICAL AHS (HAHS) to save communication bandwidth as second extension of the AHS. For the first extension, we use a machine learning approach for gradually learning the hormone values of different tasks. This is a major advance because expert knowledge is needed to configure the AHS up to now. We present an observer/controller architecture as an extension of the AHS to monitor and control its behavior. The user has to provide a simple set of initial rules, and the observer/controller is able to generate new rules if needed. The evaluation of our approach using a benchmark (containing six different types of tasks) shows that the observer/controller is able to match the goals provided by the user, and we discuss it in detail. The second extension is the hierarchical AHS where the PEs of the system consist of several different clusters each of them having its own communication infrastructure, for example, a bus system. The HAHS is able to save communication effort because the broadcast communication of the hormones is limited to the clusters. Nevertheless, it provides the same self‐X properties as the AHS, even the time for self‐configuration is shorter than for the AHS. We present evaluations that show that the HAHS performs better for applications with large numbers of PEs than the AHS. Copyright © 2015 John Wiley & Sons, Ltd.

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Section: Related Workmentioning

confidence: 99%

Two‐level extensions of an artificial hormone system

Pacher

2015

Concurrency and Computation

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“…In next paper, Implementation and Evaluation of a Self‐Organizing Artificial Hormone System to Assign Time Dependent Tasks , Mathias Pacher and Uwe Brinkschulte propose a new method to assign tasks that are connected by time dependencies within a heterogeneous environment. In this approach, the tasks composing the system are distributed by using an Artificial Hormone System that is self‐organizing and able to meet real‐time constraints.…”

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confidence: 99%

Introduction to the Special Issue: SORT 2010

Higuera-Toledano

Brinkschulte

Rettberg

2012

Concurrency and Computation

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Special Issue: Multi‐core Supported Network and System Security

Xiang

Zhou

2009

Concurrency and Computation

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Security and privacy have been the major concerns when people design computer networks and systems. In the recent years, there has been a significant increase in network and system attacks, such as frauds, distributed denial of service, viruses, worms, spyware, and malware, etc., causing huge economical and social damage. To deal with the rapidly evolving threats of today and the more intelligent and automatic threats in the future, we urgently need new security systems, at all times and in real-time, to protect the networks and systems, without causing performance penalty to normal operations.Multi-core processors represent a major evolution in computing hardware technology. Whereas two years ago most network processors and personal computer microprocessors had single core configuration, the majority of the current microprocessors contain dual or quad cores and the number of cores on die is expected to grow exponentially over time. Multi-core provides an application with more processing power from the hardware perspective. However, there are still significant software design challenges that must be overcome before the real-time defense system can be realized. The difficulty is not in building multi-core hardware, but in concurrently programming security systems in a way that lets them benefit from the continued growth in the CPU performance.Building such a multi-core-supported security system faces significant challenges, such as

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Implementation and evaluation of a self‐organizing artificial hormone system to assign time‐dependent tasks

Cited by 7 publications

References 18 publications

Two‐level extensions of an artificial hormone system

Two‐level extensions of an artificial hormone system

Introduction to the Special Issue: SORT 2010

Special Issue: Multi‐core Supported Network and System Security

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