Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.24
Sultan H. Almotiri, M. Khan, Mohammad A. Alghamdi
In this paper we describe the mobile health (m-health) system in the context of Internet of Things (IoT). We describe the fundamental characteristics of m-health devices such as compactness, IP connectivity, low-power consumption and security. We discuss acquisition of mobile health data via medical gadgets and wearables and application of this data in monitoring various health conditions such as blood sugar level, ECG, blood-pressure, asthma, etc. Security is very critical for IoT based m-health system. We address the issues of confidentiality, privacy, and security in the context of secure m-health system. We listed several measures to protect the information of patients and m-health system. The m-health system will benefit the patients in many ways such as quick diagnosis, remote monitoring and home rehabilitation. Overall m-health system will significantly reduces healthcare cost and unnecessary hospitalizations.
{"title":"Mobile Health (m-Health) System in the Context of IoT","authors":"Sultan H. Almotiri, M. Khan, Mohammad A. Alghamdi","doi":"10.1109/W-FiCloud.2016.24","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.24","url":null,"abstract":"In this paper we describe the mobile health (m-health) system in the context of Internet of Things (IoT). We describe the fundamental characteristics of m-health devices such as compactness, IP connectivity, low-power consumption and security. We discuss acquisition of mobile health data via medical gadgets and wearables and application of this data in monitoring various health conditions such as blood sugar level, ECG, blood-pressure, asthma, etc. Security is very critical for IoT based m-health system. We address the issues of confidentiality, privacy, and security in the context of secure m-health system. We listed several measures to protect the information of patients and m-health system. The m-health system will benefit the patients in many ways such as quick diagnosis, remote monitoring and home rehabilitation. Overall m-health system will significantly reduces healthcare cost and unnecessary hospitalizations.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131308185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.28
F. Dalipi, Sule YAYILGAN YILDIRIM
The emergence and evolution of Internet of Things (IoT) offers great advantages to improve substantially the management over electricity consumption and distribution to the benefit of consumers, suppliers and grid operators. However, introducing IoT related devices and technologies in smart grids might lead to new security and privacy challenges. Though necessary technological innovations to ensure secure communication are being developed, more work is still required towards more secure standards for communication between devices and Smart Grids. This paper provides an overview about the security and privacy challenges of IoT applications in smart grids. Furthermore, we highlight and analyze some solutions and practices being used to cope with security and privacy requirements for IoT on deployment and management of smart grid. We address three types of challenge domains: customer domain, information and communication domain, and the grid domain.
{"title":"Security and Privacy Considerations for IoT Application on Smart Grids: Survey and Research Challenges","authors":"F. Dalipi, Sule YAYILGAN YILDIRIM","doi":"10.1109/W-FiCloud.2016.28","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.28","url":null,"abstract":"The emergence and evolution of Internet of Things (IoT) offers great advantages to improve substantially the management over electricity consumption and distribution to the benefit of consumers, suppliers and grid operators. However, introducing IoT related devices and technologies in smart grids might lead to new security and privacy challenges. Though necessary technological innovations to ensure secure communication are being developed, more work is still required towards more secure standards for communication between devices and Smart Grids. This paper provides an overview about the security and privacy challenges of IoT applications in smart grids. Furthermore, we highlight and analyze some solutions and practices being used to cope with security and privacy requirements for IoT on deployment and management of smart grid. We address three types of challenge domains: customer domain, information and communication domain, and the grid domain.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131368736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.63
Keshav Bahadoor, Patrick Hosein
In today's highly technology-based world, wireless devices such as smartphones, are being utilized for solving daily problems and in making our daily lives more efficient. Although smartphones are sometimes to be blamed for vehicular accidents, they can also be used for helping to avoid accidents. In this paper we consider one such possible solution (called Project Drive), in which a smartphone based application is used to bridge the gap between negative driving detection and user motivation for safer driving behavior. Project Drive leverages a hosted web service to support the Android based application. Weather data is integrated with a modular negative driving detection component to create a point based system where positive driving is rewarded. Project Drive employs user motivation and retention strategies, such as gamification and social networking, as a means to promote safe driving. Users gain badges based on positive driving events that are seen by their contacts via the in-application social feed. Points of interest, including positive driving event areas, are visible via an interactive map. A small scale prototype was developed and used for testing of the associated algorithms as well as the social aspects of the framework.
{"title":"Application for the Detection of Dangerous Driving and an Associated Gamification Framework","authors":"Keshav Bahadoor, Patrick Hosein","doi":"10.1109/W-FiCloud.2016.63","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.63","url":null,"abstract":"In today's highly technology-based world, wireless devices such as smartphones, are being utilized for solving daily problems and in making our daily lives more efficient. Although smartphones are sometimes to be blamed for vehicular accidents, they can also be used for helping to avoid accidents. In this paper we consider one such possible solution (called Project Drive), in which a smartphone based application is used to bridge the gap between negative driving detection and user motivation for safer driving behavior. Project Drive leverages a hosted web service to support the Android based application. Weather data is integrated with a modular negative driving detection component to create a point based system where positive driving is rewarded. Project Drive employs user motivation and retention strategies, such as gamification and social networking, as a means to promote safe driving. Users gain badges based on positive driving events that are seen by their contacts via the in-application social feed. Points of interest, including positive driving event areas, are visible via an interactive map. A small scale prototype was developed and used for testing of the associated algorithms as well as the social aspects of the framework.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131852064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.77
Pınar Kırcı
In the paper, vehicle routing problem (VRP) with time windows is examined over google maps. The google maps is used to have real routes, in addition to the routes that are produced and illustrated over graphs. During the delivery process, carbon dioxide (Co2) emission rates and cost rates are examined in addition to main factors, time windows, vehicle speed, customer demands and vehicle capacity. In green energy, diminishing Co2 emission rates is a vital problem. In the paper, the best path is proposed with minimizing the cost and Co21 emissions by using the VRP with Tabu search. The paper includes an application for logistic management companies. Real scenarios are illustrated to collect results about logistics in Turkey.
{"title":"On the Performance of Tabu Search Algorithm for the Vehicle Routing Problem with Time Windows","authors":"Pınar Kırcı","doi":"10.1109/W-FiCloud.2016.77","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.77","url":null,"abstract":"In the paper, vehicle routing problem (VRP) with time windows is examined over google maps. The google maps is used to have real routes, in addition to the routes that are produced and illustrated over graphs. During the delivery process, carbon dioxide (Co2) emission rates and cost rates are examined in addition to main factors, time windows, vehicle speed, customer demands and vehicle capacity. In green energy, diminishing Co2 emission rates is a vital problem. In the paper, the best path is proposed with minimizing the cost and Co21 emissions by using the VRP with Tabu search. The paper includes an application for logistic management companies. Real scenarios are illustrated to collect results about logistics in Turkey.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134229904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.46
I. García, Ruben Casado, A. Bouchachia
In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.
{"title":"An Incremental Approach for Real-Time Big Data Visual Analytics","authors":"I. García, Ruben Casado, A. Bouchachia","doi":"10.1109/W-FiCloud.2016.46","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.46","url":null,"abstract":"In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129916071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.26
Hadi Hashem, D. Ranc
Exabytes of data are created everyday based on the generated user information over Internet. Social networks, mobile devices, emails, blogs, videos, banking transactions and others, are now establishing a new digital channel between the brands and their audiences. Powerful tools are needed to store and explore this daily expanding data, in order to submit an easy and reliable processing of user information. Traditional modeling tools face their limits in this challenge, as the information keeps growing in volume and variety. That can be handled only by non-relational data models. From 10 years, document oriented data model is shaking up the standard relation data model. We will present in this paper an evaluation of this model using a set of predefined criteria.
{"title":"Evaluating NoSQL Document Oriented Data Model","authors":"Hadi Hashem, D. Ranc","doi":"10.1109/W-FiCloud.2016.26","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.26","url":null,"abstract":"Exabytes of data are created everyday based on the generated user information over Internet. Social networks, mobile devices, emails, blogs, videos, banking transactions and others, are now establishing a new digital channel between the brands and their audiences. Powerful tools are needed to store and explore this daily expanding data, in order to submit an easy and reliable processing of user information. Traditional modeling tools face their limits in this challenge, as the information keeps growing in volume and variety. That can be handled only by non-relational data models. From 10 years, document oriented data model is shaking up the standard relation data model. We will present in this paper an evaluation of this model using a set of predefined criteria.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"94 6 Pt 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129533002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.27
P. Balco, M. Drahosová
The issue of knowledge management is crucial for any organization. Convenient access to the requested content is creating a competitive advantage for different types of decisions. Today, when we are inundated with large volumes of information it is essential to use technological solutions that enable flexible storage, retrieval, processing and interpreting information. One of approach, which is communicated a few years, but it implementation is hampered by distrust are solutions based on cloud technology. Their potential grow particularly in an environment where individual skills are shared to a large number of users.
{"title":"Knowledge Management as a Service (KMaaS)","authors":"P. Balco, M. Drahosová","doi":"10.1109/W-FiCloud.2016.27","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.27","url":null,"abstract":"The issue of knowledge management is crucial for any organization. Convenient access to the requested content is creating a competitive advantage for different types of decisions. Today, when we are inundated with large volumes of information it is essential to use technological solutions that enable flexible storage, retrieval, processing and interpreting information. One of approach, which is communicated a few years, but it implementation is hampered by distrust are solutions based on cloud technology. Their potential grow particularly in an environment where individual skills are shared to a large number of users.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126771715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.44
Takamitsu Shioi, K. Hatano
Database systems have recently utilized both row-and a column-oriented storage systems, also termed as hybrid storage, as their storage devices for large scale data management. The hybrid storage based database systems should ideally be operated on distributed computing environments for query optimization, however, studies on query optimization of such database systems are not available in literature. Therefore, the selection of the storage type and the accurate estimation of query workload are critical factors for efficient query processing on distributed computing environments. In this paper, we describe a novel storage selection method of a RDBMS with a column-oriented storage function, which is a type of DBMSs with the hybrid storage, on distributed computing environments. Our storage selection method is designed for efficient query processing based on rule-and cost-based optimization in the research field of RDBMS, and it can help to improve query optimization of RDBMSs with the hybrid storage.
{"title":"Rule- and Cost-Based Optimization of OLAP Workloads on Distributed RDBMS with Column-Oriented Storage Function","authors":"Takamitsu Shioi, K. Hatano","doi":"10.1109/W-FiCloud.2016.44","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.44","url":null,"abstract":"Database systems have recently utilized both row-and a column-oriented storage systems, also termed as hybrid storage, as their storage devices for large scale data management. The hybrid storage based database systems should ideally be operated on distributed computing environments for query optimization, however, studies on query optimization of such database systems are not available in literature. Therefore, the selection of the storage type and the accurate estimation of query workload are critical factors for efficient query processing on distributed computing environments. In this paper, we describe a novel storage selection method of a RDBMS with a column-oriented storage function, which is a type of DBMSs with the hybrid storage, on distributed computing environments. Our storage selection method is designed for efficient query processing based on rule-and cost-based optimization in the research field of RDBMS, and it can help to improve query optimization of RDBMSs with the hybrid storage.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129782365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.29
Hamad Al-Mohannadi, Q. A. K. Mirza, A. P. Namanya, I. Awan, A. Cullen, Jules Pagna Disso
Cyber attack is a sensitive issue in the world of Internet security. Governments and business organisations around the world are providing enormous effort to secure their data. They are using various types of tools and techniques to keep the business running, while adversaries are trying to breach security and send malicious software such as botnets, viruses, trojans etc., to access valuable data. Everyday the situation is getting worse because of new types of malware emerging to attack networks. It is important to understand those attacks both before and after they happen in order to provide better security to our systems. Understanding attack models provide more insight into network vulnerability, which in turn can be used to protect the network from future attacks. In the cyber security world, it is difficult to predict a potential attack without understanding the vulnerability of the network. So, it is important to analyse the network to identify top possible vulnerability list, which will give an intuitive idea to protect the network. Also, handling an ongoing attack poses significant risk on the network and valuable data, where prompt action is necessary. Proper utilisation of attack modelling techniques provide advance planning, which can be implemented rapidly during an ongoing attack event. This paper aims to analyse various types of existing attack modelling techniques to understand the vulnerability of the network, and the behaviour and goals of the adversary. The ultimate goal is to handle cyber attack in efficient manner using attack modelling techniques.
{"title":"Cyber-Attack Modeling Analysis Techniques: An Overview","authors":"Hamad Al-Mohannadi, Q. A. K. Mirza, A. P. Namanya, I. Awan, A. Cullen, Jules Pagna Disso","doi":"10.1109/W-FiCloud.2016.29","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.29","url":null,"abstract":"Cyber attack is a sensitive issue in the world of Internet security. Governments and business organisations around the world are providing enormous effort to secure their data. They are using various types of tools and techniques to keep the business running, while adversaries are trying to breach security and send malicious software such as botnets, viruses, trojans etc., to access valuable data. Everyday the situation is getting worse because of new types of malware emerging to attack networks. It is important to understand those attacks both before and after they happen in order to provide better security to our systems. Understanding attack models provide more insight into network vulnerability, which in turn can be used to protect the network from future attacks. In the cyber security world, it is difficult to predict a potential attack without understanding the vulnerability of the network. So, it is important to analyse the network to identify top possible vulnerability list, which will give an intuitive idea to protect the network. Also, handling an ongoing attack poses significant risk on the network and valuable data, where prompt action is necessary. Proper utilisation of attack modelling techniques provide advance planning, which can be implemented rapidly during an ongoing attack event. This paper aims to analyse various types of existing attack modelling techniques to understand the vulnerability of the network, and the behaviour and goals of the adversary. The ultimate goal is to handle cyber attack in efficient manner using attack modelling techniques.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130392465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-08-01DOI: 10.1109/W-FiCloud.2016.57
Mohammed N. Alandoli, M. Al-Ayyoub, Mohammad Al-Smadi, Y. Jararweh, E. Benkhelifa
Social Network Analysis (SNA) has been gaining a lot of attention lately. One of the common steps in SNA is community detection. SNA literature has many interesting algorithms for community detection. One of the popular ones was proposed by Newman and it is mainly revolved around using a clustering algorithm. Three phases are iteratively applied in this algorithm in order to find the "best" community structure. These phases are: spectral mapping, clustering and modularity computation. Despite its effectiveness, this method suffers greatly in terms of running time when dealing with largescale networks. A parallel implementation using GPUs is one of the feasible solutions to address this problem. Moreover, due to the iterative nature of this algorithm, dynamic parallelism lends itself as a very appealing solution. Dynamic parallelism is a novel parallel programming technique that refers to the ability to launch new grids from the GPU. In this work, we present three implementation of the clustering-based community detection algorithm. In addition to the sequential implementation, we present two implementations: a Hybrid CPU-GPU (HCG) one and a Dynamic Parallel (DP) one. We test our parallel implementations on benchmark datasets to show the speed-up of each parallel implementation compared with the sequential one. The results show that the DP implementation achieves good speed-ups reaching up to 4.45X, however, the speed-ups achieved by HCG are almost twice as much.
{"title":"Using Dynamic Parallelism to Speed Up Clustering-Based Community Detection in Social Networks","authors":"Mohammed N. Alandoli, M. Al-Ayyoub, Mohammad Al-Smadi, Y. Jararweh, E. Benkhelifa","doi":"10.1109/W-FiCloud.2016.57","DOIUrl":"https://doi.org/10.1109/W-FiCloud.2016.57","url":null,"abstract":"Social Network Analysis (SNA) has been gaining a lot of attention lately. One of the common steps in SNA is community detection. SNA literature has many interesting algorithms for community detection. One of the popular ones was proposed by Newman and it is mainly revolved around using a clustering algorithm. Three phases are iteratively applied in this algorithm in order to find the \"best\" community structure. These phases are: spectral mapping, clustering and modularity computation. Despite its effectiveness, this method suffers greatly in terms of running time when dealing with largescale networks. A parallel implementation using GPUs is one of the feasible solutions to address this problem. Moreover, due to the iterative nature of this algorithm, dynamic parallelism lends itself as a very appealing solution. Dynamic parallelism is a novel parallel programming technique that refers to the ability to launch new grids from the GPU. In this work, we present three implementation of the clustering-based community detection algorithm. In addition to the sequential implementation, we present two implementations: a Hybrid CPU-GPU (HCG) one and a Dynamic Parallel (DP) one. We test our parallel implementations on benchmark datasets to show the speed-up of each parallel implementation compared with the sequential one. The results show that the DP implementation achieves good speed-ups reaching up to 4.45X, however, the speed-ups achieved by HCG are almost twice as much.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117187205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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