An Energy-Aware Algorithm for Large Scale Foraging Systems
نویسندگان
چکیده
The foraging task is one of the canonical testbeds for cooperative robotics, in which a collection of coordinated robots have to find and transport one or more objects to one or more specific storage points. Swarm robotics has been widely considered in such situations, due to its strengths such as robustness, simplicity and scalability. Typical multi-robot foraging systems currently consider tens to hundreds of agents. This paper presents a new algorithm called Energy-aware Cooperative Switching Algorithm for Foraging (EC-SAF) that manages thousands of robots. We investigate therefore the scalability of EC-SAF algorithm and the parameters that can affect energy efficiency overtime. Results indicate that EC-SAF is scalable and effective in reducing swarm energy consumption compared to an energy-aware version of the reference well-known c-marking algorithm (Ec-marking).
منابع مشابه
Green Energy-aware task scheduling using the DVFS technique in Cloud Computing
Nowdays, energy consumption as a critical issue in distributed computing systems with high performance has become so green computing tries to energy consumption, carbon footprint and CO2 emissions in high performance computing systems (HPCs) such as clusters, Grid and Cloud that a large number of parallel. Reducing energy consumption for high end computing can bring various benefits such as red...
متن کاملبرنامهریزی تولید همزمان انرژی الکتریکی و حرارتی با درنظرگرفتن اثر دریچههای بخار و نواحی ممنوعۀ تولید توسط الگوریتم ترکیبی BF-PSO
Combined heat and power production technology has energy efficiency and environmental advantages over other forms of energy supply. Solving combined heat and power economic dispatch problem considering all system demand and operational constraints determines optimal utilization of power and heat sources. In micro grids, dual dependency of combined heat and power production makes economic dispat...
متن کاملSubstation Expansion Planning Based on BFOA
In recent years, significant research efforts have been devoted to the optimal planning of power systems. Substation Expansion Planning (SEP) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. The large number of design variables, and combination of discrete ...
متن کاملE2DR: Energy Efficient Data Replication in Data Grid
Abstract— Data grids are an important branch of gird computing which provide mechanisms for the management of large volumes of distributed data. Energy efficiency has recently emerged as a hot topic in large distributed systems. The development of computing systems is traditionally focused on performance improvements driven by the demand of client's applications in scientific and business domai...
متن کاملAdaptive Dynamic Data Placement Algorithm for Hadoop in Heterogeneous Environments
Hadoop MapReduce framework is an important distributed processing model for large-scale data intensive applications. The current Hadoop and the existing Hadoop distributed file system’s rack-aware data placement strategy in MapReduce in the homogeneous Hadoop cluster assume that each node in a cluster has the same computing capacity and a same workload is assigned to each node. Default Hadoop d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Scalable Computing: Practice and Experience
دوره 16 شماره
صفحات -
تاریخ انتشار 2015