The Experts below are selected from a list of 19344 Experts worldwide ranked by ideXlab platform
John M Tracey - One of the best experts on this subject based on the ideXlab platform.
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understanding instant messaging traffic characteristics
International Conference on Distributed Computing Systems, 2007Co-Authors: Zhen Xiao, Lei Guo, John M TraceyAbstract:instant messaging (IM) has become increasingly popular due to its quick response time, its ease of use, and possibility of multitasking. It is estimated that there are several millions of instant messaging users who use IM for various purposes: simple requests and responses, scheduling face to face meetings, or just to check the availability of colleagues and friends. Despite its popularity and user base, little has been done to characterize IM traffic. One reason might be its relatively small traffic volume, although this is changing as more users start using video or voice chats and file attachments. Moreover, all major instant messaging systems route text messages through central servers. While this facilitates firewall traversal and gives instant messaging companies more control, it creates a potential bottleneck at the instant messaging servers. This is especially so for large instant messaging operators with tens of millions of users and during flash crowd events. Another reason for the lack of previous studies is the difficulty in getting access to instant messaging traces due to privacy concerns. In this paper, we analyze the traffic of two popular instant messaging systems, AOL instant Messenger (AIM) and MSN/Windows Live Messenger, from thousands of employees in a large enterprise. We found that most instant messaging traffic is due to presence, hints, or other extraneous traffic. Chat messages constitute only a small percentage of the total IM traffic. This means, during overload, IM servers can protect the instantaneous nature of the communication by dropping extraneous traffic. We also found that the social network of lM users does not follow a power law distribution. It can be characterized by a Weibull distribution. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging workload generation.
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ICDCS - Understanding instant messaging Traffic Characteristics
27th International Conference on Distributed Computing Systems (ICDCS '07), 2007Co-Authors: Zhen Xiao, Lei Guo, John M TraceyAbstract:instant messaging (IM) has become increasingly popular due to its quick response time, its ease of use, and possibility of multitasking. It is estimated that there are several millions of instant messaging users who use IM for various purposes: simple requests and responses, scheduling face to face meetings, or just to check the availability of colleagues and friends. Despite its popularity and user base, little has been done to characterize IM traffic. One reason might be its relatively small traffic volume, although this is changing as more users start using video or voice chats and file attachments. Moreover, all major instant messaging systems route text messages through central servers. While this facilitates firewall traversal and gives instant messaging companies more control, it creates a potential bottleneck at the instant messaging servers. This is especially so for large instant messaging operators with tens of millions of users and during flash crowd events. Another reason for the lack of previous studies is the difficulty in getting access to instant messaging traces due to privacy concerns. In this paper, we analyze the traffic of two popular instant messaging systems, AOL instant Messenger (AIM) and MSN/Windows Live Messenger, from thousands of employees in a large enterprise. We found that most instant messaging traffic is due to presence, hints, or other extraneous traffic. Chat messages constitute only a small percentage of the total IM traffic. This means, during overload, IM servers can protect the instantaneous nature of the communication by dropping extraneous traffic. We also found that the social network of lM users does not follow a power law distribution. It can be characterized by a Weibull distribution. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging workload generation.
Zhen Xiao - One of the best experts on this subject based on the ideXlab platform.
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understanding instant messaging traffic characteristics
International Conference on Distributed Computing Systems, 2007Co-Authors: Zhen Xiao, Lei Guo, John M TraceyAbstract:instant messaging (IM) has become increasingly popular due to its quick response time, its ease of use, and possibility of multitasking. It is estimated that there are several millions of instant messaging users who use IM for various purposes: simple requests and responses, scheduling face to face meetings, or just to check the availability of colleagues and friends. Despite its popularity and user base, little has been done to characterize IM traffic. One reason might be its relatively small traffic volume, although this is changing as more users start using video or voice chats and file attachments. Moreover, all major instant messaging systems route text messages through central servers. While this facilitates firewall traversal and gives instant messaging companies more control, it creates a potential bottleneck at the instant messaging servers. This is especially so for large instant messaging operators with tens of millions of users and during flash crowd events. Another reason for the lack of previous studies is the difficulty in getting access to instant messaging traces due to privacy concerns. In this paper, we analyze the traffic of two popular instant messaging systems, AOL instant Messenger (AIM) and MSN/Windows Live Messenger, from thousands of employees in a large enterprise. We found that most instant messaging traffic is due to presence, hints, or other extraneous traffic. Chat messages constitute only a small percentage of the total IM traffic. This means, during overload, IM servers can protect the instantaneous nature of the communication by dropping extraneous traffic. We also found that the social network of lM users does not follow a power law distribution. It can be characterized by a Weibull distribution. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging workload generation.
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ICDCS - Understanding instant messaging Traffic Characteristics
27th International Conference on Distributed Computing Systems (ICDCS '07), 2007Co-Authors: Zhen Xiao, Lei Guo, John M TraceyAbstract:instant messaging (IM) has become increasingly popular due to its quick response time, its ease of use, and possibility of multitasking. It is estimated that there are several millions of instant messaging users who use IM for various purposes: simple requests and responses, scheduling face to face meetings, or just to check the availability of colleagues and friends. Despite its popularity and user base, little has been done to characterize IM traffic. One reason might be its relatively small traffic volume, although this is changing as more users start using video or voice chats and file attachments. Moreover, all major instant messaging systems route text messages through central servers. While this facilitates firewall traversal and gives instant messaging companies more control, it creates a potential bottleneck at the instant messaging servers. This is especially so for large instant messaging operators with tens of millions of users and during flash crowd events. Another reason for the lack of previous studies is the difficulty in getting access to instant messaging traces due to privacy concerns. In this paper, we analyze the traffic of two popular instant messaging systems, AOL instant Messenger (AIM) and MSN/Windows Live Messenger, from thousands of employees in a large enterprise. We found that most instant messaging traffic is due to presence, hints, or other extraneous traffic. Chat messages constitute only a small percentage of the total IM traffic. This means, during overload, IM servers can protect the instantaneous nature of the communication by dropping extraneous traffic. We also found that the social network of lM users does not follow a power law distribution. It can be characterized by a Weibull distribution. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging workload generation.
Lei Guo - One of the best experts on this subject based on the ideXlab platform.
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understanding instant messaging traffic characteristics
International Conference on Distributed Computing Systems, 2007Co-Authors: Zhen Xiao, Lei Guo, John M TraceyAbstract:instant messaging (IM) has become increasingly popular due to its quick response time, its ease of use, and possibility of multitasking. It is estimated that there are several millions of instant messaging users who use IM for various purposes: simple requests and responses, scheduling face to face meetings, or just to check the availability of colleagues and friends. Despite its popularity and user base, little has been done to characterize IM traffic. One reason might be its relatively small traffic volume, although this is changing as more users start using video or voice chats and file attachments. Moreover, all major instant messaging systems route text messages through central servers. While this facilitates firewall traversal and gives instant messaging companies more control, it creates a potential bottleneck at the instant messaging servers. This is especially so for large instant messaging operators with tens of millions of users and during flash crowd events. Another reason for the lack of previous studies is the difficulty in getting access to instant messaging traces due to privacy concerns. In this paper, we analyze the traffic of two popular instant messaging systems, AOL instant Messenger (AIM) and MSN/Windows Live Messenger, from thousands of employees in a large enterprise. We found that most instant messaging traffic is due to presence, hints, or other extraneous traffic. Chat messages constitute only a small percentage of the total IM traffic. This means, during overload, IM servers can protect the instantaneous nature of the communication by dropping extraneous traffic. We also found that the social network of lM users does not follow a power law distribution. It can be characterized by a Weibull distribution. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging workload generation.
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ICDCS - Understanding instant messaging Traffic Characteristics
27th International Conference on Distributed Computing Systems (ICDCS '07), 2007Co-Authors: Zhen Xiao, Lei Guo, John M TraceyAbstract:instant messaging (IM) has become increasingly popular due to its quick response time, its ease of use, and possibility of multitasking. It is estimated that there are several millions of instant messaging users who use IM for various purposes: simple requests and responses, scheduling face to face meetings, or just to check the availability of colleagues and friends. Despite its popularity and user base, little has been done to characterize IM traffic. One reason might be its relatively small traffic volume, although this is changing as more users start using video or voice chats and file attachments. Moreover, all major instant messaging systems route text messages through central servers. While this facilitates firewall traversal and gives instant messaging companies more control, it creates a potential bottleneck at the instant messaging servers. This is especially so for large instant messaging operators with tens of millions of users and during flash crowd events. Another reason for the lack of previous studies is the difficulty in getting access to instant messaging traces due to privacy concerns. In this paper, we analyze the traffic of two popular instant messaging systems, AOL instant Messenger (AIM) and MSN/Windows Live Messenger, from thousands of employees in a large enterprise. We found that most instant messaging traffic is due to presence, hints, or other extraneous traffic. Chat messages constitute only a small percentage of the total IM traffic. This means, during overload, IM servers can protect the instantaneous nature of the communication by dropping extraneous traffic. We also found that the social network of lM users does not follow a power law distribution. It can be characterized by a Weibull distribution. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging workload generation.
Erik Rolland - One of the best experts on this subject based on the ideXlab platform.
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Understanding individual adoption of mobile instant messaging: a multiple perspectives approach
Information Technology and Management, 2015Co-Authors: Cheolho Yoon, Changyun Jeong, Erik RollandAbstract:Use of mobile instant messaging has grown tremendously in the last few years, and is positioned as a platform for mobile business. This study aims to explore how an individual’s intention to use mobile instant messaging is influenced by technical and individual characteristics as well as social influence factors. A research model based on perceived usefulness and perceived enjoyment, including technical characteristics (ease of use and convenience), individual characteristics (computer playfulness and personal innovativeness), and social influence factors (perceived critical mass and identification) was developed. The model was empirically analyzed using structural equation modeling with data from mobile instant messaging service users in Korea. The results indicate that most of the proposed technical characteristics, individual characteristics, and social influence factors have impacts on perceived usefulness and/or perceived enjoyment, which form the intention to use mobile instant messaging. Our findings provide strategic guidelines for service providers with respect to the development and operations of mobile instant messaging.
Hao Wang - One of the best experts on this subject based on the ideXlab platform.
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IWCMC - instant messaging Tool Task Collaboration Platform
2020 International Wireless Communications and Mobile Computing (IWCMC), 2020Co-Authors: Dapeng Zhou, Ran Ran, Xing Huang, Zhuangguan Yang, Hao WangAbstract:With the development of E-mail technology, instant messaging technology and desktop conferencing systems, computer-supported collaboration plays an important role in the use of computers today. In recent years, with the rapid development of instant messaging technology, the network virtual community formed on the Internet by using instant messaging system has attracted more and more people to join. The flexible and powerful chat function enables users in different places to communicate face to face. The purpose of this paper is to study and realize the multimedia collaborative communication system integrated with voice and instant communication, and to build a new generation of enterprise-level collaborative office interaction platform. In order to meet the needs of enterprises of different sizes, this system adopts cloud architecture design, which can not only support a single large enterprise, but also provide communication services to many small and medium-sized enterprises by means of virtual enterprise. Implement a enterprise instant messaging system based on the design for the purpose, through the in-depth study of instant messaging system, understand the characteristics and the future development trend of instant messaging system, thus further chosen on the basis of open source server Openfire for secondary development, in the form of a plug-in functionality extensions, complete the final goal, the practice has proved that it is feasible.
