CDS-MIP: CDS-based Multiple Itineraries Planning for mobile agents in wireless sensor network

using multi agents in the wireless sensor networks (WSNs) for aggregating data has gained significant attention. Planning the optimal itinerary of the mobile agent is an essential step before the process of data gathering. Many approaches have been proposed to solve the problem of planning MAs itineraries, but all of those approaches are assuming that the MAs visit all SNs and large number of intermediate nodes. This assumption imposed a burden; the size of agent increases with the increase in the visited SNs, therefore consume more energy and spend more time in its migration. None of those proposed approaches takes into account the significant role that the connected dominating nodes play as virtual infrastructure in such wireless sensor networks WSNs. This article introduces a novel energy-efficient itinerary planning algorithmic approach based on the minimum connected dominating sets (CDSs) for multi-agents dedicated in data gathering process. In our proposed approach, instead of planning the itineraries over all sensor nodes SNs, we plan the itineraries among subsets of the MCDS in each cluster. Thus, no need to move the agent in all the SNs, and the intermediate nodes (if any) in each itinerary will be few. Simulation results have demonstrated that our approach is more efficient than other approaches in terms of overall energy consumption and task execution time

A new Itinerary planning approach among multiple mobile agents in wireless sensor networks (WSN) to reduce energy consumption

one of the important challenges in wireless sensors networks (WSN) resides in energy consumption. In order to resolve this limitation, several solutions were proposed. Recently, the exploitation of mobile agent technologies in wireless sensor networks to optimize energy consumption attracts researchers. Despite their advantage as an ambitious solution, the itineraries followed by migrating mobile agents can surcharge the network and so have an impact on energy consumption. Many researches have dealt with itinerary planning in WSNs through the use of a single agent (SIP: Single agent Itinerary Planning) or multiple mobile agents (MIP: Multiple agents Itinerary Planning). However, the use of multi-agents causes the emergence of the data load unbalancing problem among mobile agents, where the geographical distance is the unique factor motivating to plan the itinerary of the agents. The data balancing factor has an important role especially in Wireless sensor networks multimedia that owns a considerable volume of data size. It helps to optimize the tasks duration and thus optimizes the overall answer time of the network.  In this paper, we provide a new MIP solution (GIGM-MIP) which is based not only on geographic information but also on the amount of data provided by each node to reduce the energy consumption of the network. The simulation experiments show that our approach is more efficient than other approaches in terms of task duration and the amount of energy consumption

Determination of Itinerary Planning for Multiple Agents in Wireless Sensor Networks

The mobile agent is a new technology in wireless sensor networks that outperforms the traditional client/server architecture in terms of energy consumption, end to end delay and packet delivery ratio. Single mobile agent will not be efficient for large scale networks. Therefore, the use of multiple mobile agents will be an excellent solution to resolve the problem of the task duration especially for this kind of networks. The itinerary planning of mobile agents represents the main challenge to achieve the trade-off between energy consumption and end to end delay. In this article we present a new algorithm named Optimal Multi-Agents Itinerary Planning (OMIP). The source nodes are grouped into clusters and the sink sends a mobile agent to the cluster head of every cluster; which migrates between source nodes, collects and aggregates data before returning to the sink. The results of the simulations testify the efficiency of our algorithm against the existing algorithms of multi-agent itinerary planning. The performance gain is evident in terms of energy consumption, accumulated hop count and end to end delay of the tasks in the network

(So) Big Data and the transformation of the city

The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders in building knowledge discovery pipelines over such data sources. At the same time, this widespread data availability also raises privacy issues that must be considered by both industrial and academic stakeholders. In this paper, we provide a wide perspective on the role that big data have in reshaping cities. The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media. In discussing these aspects, we leverage, as concrete examples and case studies of urban data science tools, the results obtained in the “City of Citizens” thematic area of the Horizon 2020 SoBigData initiative, which includes a virtual research environment with mobility datasets and urban analytics methods developed by several institutions around Europe. We conclude the paper outlining the main research challenges that urban data science has yet to address in order to help make the smart city vision a reality

Pemodelan Sistem Multiagent pada Wireless Sensor Network

Wireless Sensor Network (WSN) merupakan perangkat embedded kecil yang dipasang di jaringan skala besar yang memiliki kapabilitas penginderaan, komputasi, dan komunikasi. WSN mengkombinasikan teknologi sensor modern, teknologi micro electronic, komputasi, teknologi komunikasi, dan pemrosesan terdistribusi. Implementasi sistem multiagent pada WSN cukup menjanjikan untuk meningkatkan efektifitas dan efisiensi kerja WSN. Namun, penelitian yang dilakukan terkait sistem multiagent di WSN masih parsial dengan kata lain terlalu fokus pada isu-isu tertentu. Paper ini mendeskripsikan penelitian terkait dengan penerapan sistem multiagent di WSN yang memperhatikan berbagai aspek pendukung untuk efektifitas dan efisiensi agent seperti arsitektur organisasi multiagent, itinerary planning, kapabilitas agent, middleware, dan platform hardware yang digunakan. Metodologi yang digunakan adalah INGENIAS yang berbasis pada agent-oriented software enginering

Analisis Dan Desain Sistem Multiagent Pada Sensor Wireless

Wireless Sensor atau Wireless Sensor Network (WSN) merupakan perangkat embedded kecil yang dipasang di jaringan skala besar yang memiliki kapabilitas penginderaan, komputasi, dan komunikasi. WSN mengkombinasikan teknologi sensor modern, teknologi micro electronic, komputasi, teknologi komunikasi, dan pemrosesan terdistribusi. Implementasi sistem multiagent pada WSN cukup menjanjikan untuk meningkatkan efektifitas dan efisiensi kerja WSN. Namun, penelitian yang dilakukan terkait sistem multiagent di WSN masih parsial dengan kata lain terlalu fokus pada isu-isu tertentu. Paper ini mendeskripsikan penelitian terkait dengan penerapan sistem multiagent di WSN yang memperhatikan berbagai aspek pendukung untuk efektifitas dan efisiensi agent seperti arsitektur organisasi multiagent, itinerary planning, kapabilitas agent, middleware dan platform hardware yang digunakan. Metodologi yang digunakan adalah Ingenias yang berbasis pada agent oriented software engineering.Kata Kunci: Agent, Ingenias, Itinerary, Multiagent, Wireless Sensor Network. PENDAHULUANPerkembangan teknologi sensor semakin pesat dengan kapabilitas tidak hanya pada aspek pengindraan dan signal acquisition, namun memiliki kapabilitas dalam melakukan komputasi dan komunikasi dengan perangkat lainnya. Sensor ini dinamakan sebagai Wireless Sensor Network (WSN) yang juga memanfaatkan teknologi internet sebagai media komunikasinya. WSN memiliki beberapa karakteristik seperti alokasi energy dan bandwidth terbatas, unattended ad hoc deployment, cakupan skala luas, high noise dan fault rate, lingkungan yang dinamis dan tak menentu, serta memberikan dampak pada pengembangan aplikasi yang variatif seperti structural monitoring, bio-habitat monitoring, industrial monitoring, disaster management, military surveillence, dan building security. Karakteristik ini memberikan tantangan bagi pengembangan WSN. Saat ini WSN di-deploy dengan pendekatan client-server.Menurut Min Chen, et al pendekatan ini merupakan metode tradisional penyebaran data di WSN. Kemunculan event me-trigger node-node sumber di sekitarnya untuk mengumpulkan dan mengirim data ke sink sendiri. Jumlah aliran data umumnya sama dengan jumlah node-node sumber sehingga menyebabkan konsumsi bandwidth dan energi yang cukup tinggi. Pendekatan ini menyebabkan ketidakseimbangan konsumsi energi di jaringan karena node-node yang lebih dekat dengan sink akan mengirim lebih banyak data, yaitu data miliknya maupun data yang dititipkan dari node lain. Untuk itu, diperlukan pendekatan lain yang dapat menyelesaikan permasalahan di atas, yaitu salah satunya dengan pendekatan sistem mobile agent