The Experts below are selected from a list of 12414 Experts worldwide ranked by ideXlab platform
Shihlung Shaw - One of the best experts on this subject based on the ideXlab platform.
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estimating potential demand of bicycle trips from mobile phone data an Anchor Point based approach
ISPRS international journal of geo-information, 2016Co-Authors: Shihlung Shaw, Zhixiang Fang, Ling YinAbstract:This study uses a large-scale mobile phone dataset to estimate potential demand of bicycle trips in a city. By identifying two important Anchor Points (night-time Anchor Point and day-time Anchor Point) from individual cellphone trajectories, this study proposes an Anchor-Point based trajectory segmentation method to partition cellphone trajectories into trip chain segments. By selecting trip chain segments that can potentially be served by bicycles, two indicators (inflow and outflow) are generated at the cellphone tower level to estimate the potential demand of incoming and outgoing bicycle trips at different places in the city and different times of a day. A maximum coverage location-allocation model is used to suggest locations of bike sharing stations based on the total demand generated at each cellphone tower. Two measures are introduced to further understand characteristics of the suggested bike station locations: (1) accessibility; and (2) dynamic relationships between incoming and outgoing trips. The accessibility measure quantifies how well the stations could serve bicycle users to reach other potential activity destinations. The dynamic relationships reflect the asymmetry of human travel patterns at different times of a day. The study indicates the value of mobile phone data to intelligent spatial decision support in public transportation planning.
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understanding aggregate human mobility patterns using passive mobile phone location data a home based approach
Transportation, 2015Co-Authors: Shihlung Shaw, Ling Yin, Ziliang Zhao, Zhixiang FangAbstract:Advancements of information, communication and location-aware technologies have made collections of various passively generated datasets possible. These datasets provide new opportunities to understand human mobility patterns at a low cost and large scale. This study presents a home-based approach to understanding human mobility patterns based on a large mobile phone location dataset from Shenzhen, China. First, we estimate each individual’s “home” Anchor Point, and a modified standard distance ( $$S_{D}^{\prime }$$ ) is proposed to measure the spread of each individual’s activity space centered at this “home” Anchor Point. We then derive aggregate mobility patterns at mobile phone tower level to describe the distance distribution of $$S_{D}^{\prime }$$ for people who share the same “home” Anchor Point. A hierarchical clustering algorithm is performed and the spatial distributions of the derived clusters are analyzed to highlight areas with similar aggregate human mobility patterns. The results suggest that 43 % of the population sample travelled within a short distance ( $$S_{D}^{\prime } \le 1 \;{\text{km}}$$ ) during the 13-day study period while 23.9 % of them were associated with a large activity space ( $$S_{D}^{\prime } \ge 5 \;{\text{km}}$$ ). The geographical differences of people’s mobility patterns in Shenzhen are evident. Areas with a large proportion of people who have a small activity space mainly locate in the northern part of Shenzhen such as Baoan and Longgang districts. In the southern part where the economy is highly developed, the percentage of people with a larger activity space is higher in general. The findings could offer useful implications on policy and decision making. The proposed approach can also be used in other studies involving similar spatiotemporal datasets for travel behavior and policy analysis.
Zhixiang Fang - One of the best experts on this subject based on the ideXlab platform.
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estimating potential demand of bicycle trips from mobile phone data an Anchor Point based approach
ISPRS international journal of geo-information, 2016Co-Authors: Shihlung Shaw, Zhixiang Fang, Ling YinAbstract:This study uses a large-scale mobile phone dataset to estimate potential demand of bicycle trips in a city. By identifying two important Anchor Points (night-time Anchor Point and day-time Anchor Point) from individual cellphone trajectories, this study proposes an Anchor-Point based trajectory segmentation method to partition cellphone trajectories into trip chain segments. By selecting trip chain segments that can potentially be served by bicycles, two indicators (inflow and outflow) are generated at the cellphone tower level to estimate the potential demand of incoming and outgoing bicycle trips at different places in the city and different times of a day. A maximum coverage location-allocation model is used to suggest locations of bike sharing stations based on the total demand generated at each cellphone tower. Two measures are introduced to further understand characteristics of the suggested bike station locations: (1) accessibility; and (2) dynamic relationships between incoming and outgoing trips. The accessibility measure quantifies how well the stations could serve bicycle users to reach other potential activity destinations. The dynamic relationships reflect the asymmetry of human travel patterns at different times of a day. The study indicates the value of mobile phone data to intelligent spatial decision support in public transportation planning.
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understanding aggregate human mobility patterns using passive mobile phone location data a home based approach
Transportation, 2015Co-Authors: Shihlung Shaw, Ling Yin, Ziliang Zhao, Zhixiang FangAbstract:Advancements of information, communication and location-aware technologies have made collections of various passively generated datasets possible. These datasets provide new opportunities to understand human mobility patterns at a low cost and large scale. This study presents a home-based approach to understanding human mobility patterns based on a large mobile phone location dataset from Shenzhen, China. First, we estimate each individual’s “home” Anchor Point, and a modified standard distance ( $$S_{D}^{\prime }$$ ) is proposed to measure the spread of each individual’s activity space centered at this “home” Anchor Point. We then derive aggregate mobility patterns at mobile phone tower level to describe the distance distribution of $$S_{D}^{\prime }$$ for people who share the same “home” Anchor Point. A hierarchical clustering algorithm is performed and the spatial distributions of the derived clusters are analyzed to highlight areas with similar aggregate human mobility patterns. The results suggest that 43 % of the population sample travelled within a short distance ( $$S_{D}^{\prime } \le 1 \;{\text{km}}$$ ) during the 13-day study period while 23.9 % of them were associated with a large activity space ( $$S_{D}^{\prime } \ge 5 \;{\text{km}}$$ ). The geographical differences of people’s mobility patterns in Shenzhen are evident. Areas with a large proportion of people who have a small activity space mainly locate in the northern part of Shenzhen such as Baoan and Longgang districts. In the southern part where the economy is highly developed, the percentage of people with a larger activity space is higher in general. The findings could offer useful implications on policy and decision making. The proposed approach can also be used in other studies involving similar spatiotemporal datasets for travel behavior and policy analysis.
Ling Yin - One of the best experts on this subject based on the ideXlab platform.
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estimating potential demand of bicycle trips from mobile phone data an Anchor Point based approach
ISPRS international journal of geo-information, 2016Co-Authors: Shihlung Shaw, Zhixiang Fang, Ling YinAbstract:This study uses a large-scale mobile phone dataset to estimate potential demand of bicycle trips in a city. By identifying two important Anchor Points (night-time Anchor Point and day-time Anchor Point) from individual cellphone trajectories, this study proposes an Anchor-Point based trajectory segmentation method to partition cellphone trajectories into trip chain segments. By selecting trip chain segments that can potentially be served by bicycles, two indicators (inflow and outflow) are generated at the cellphone tower level to estimate the potential demand of incoming and outgoing bicycle trips at different places in the city and different times of a day. A maximum coverage location-allocation model is used to suggest locations of bike sharing stations based on the total demand generated at each cellphone tower. Two measures are introduced to further understand characteristics of the suggested bike station locations: (1) accessibility; and (2) dynamic relationships between incoming and outgoing trips. The accessibility measure quantifies how well the stations could serve bicycle users to reach other potential activity destinations. The dynamic relationships reflect the asymmetry of human travel patterns at different times of a day. The study indicates the value of mobile phone data to intelligent spatial decision support in public transportation planning.
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understanding aggregate human mobility patterns using passive mobile phone location data a home based approach
Transportation, 2015Co-Authors: Shihlung Shaw, Ling Yin, Ziliang Zhao, Zhixiang FangAbstract:Advancements of information, communication and location-aware technologies have made collections of various passively generated datasets possible. These datasets provide new opportunities to understand human mobility patterns at a low cost and large scale. This study presents a home-based approach to understanding human mobility patterns based on a large mobile phone location dataset from Shenzhen, China. First, we estimate each individual’s “home” Anchor Point, and a modified standard distance ( $$S_{D}^{\prime }$$ ) is proposed to measure the spread of each individual’s activity space centered at this “home” Anchor Point. We then derive aggregate mobility patterns at mobile phone tower level to describe the distance distribution of $$S_{D}^{\prime }$$ for people who share the same “home” Anchor Point. A hierarchical clustering algorithm is performed and the spatial distributions of the derived clusters are analyzed to highlight areas with similar aggregate human mobility patterns. The results suggest that 43 % of the population sample travelled within a short distance ( $$S_{D}^{\prime } \le 1 \;{\text{km}}$$ ) during the 13-day study period while 23.9 % of them were associated with a large activity space ( $$S_{D}^{\prime } \ge 5 \;{\text{km}}$$ ). The geographical differences of people’s mobility patterns in Shenzhen are evident. Areas with a large proportion of people who have a small activity space mainly locate in the northern part of Shenzhen such as Baoan and Longgang districts. In the southern part where the economy is highly developed, the percentage of people with a larger activity space is higher in general. The findings could offer useful implications on policy and decision making. The proposed approach can also be used in other studies involving similar spatiotemporal datasets for travel behavior and policy analysis.
David Candalventureira - One of the best experts on this subject based on the ideXlab platform.
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a software defined networking solution for transparent session and service continuity in dynamic multi access edge computing
IEEE Transactions on Network and Service Management, 2020Co-Authors: Pablo Fondoferreiro, Felipe Gilcastineira, F J Gonzalezcastano, David CandalventureiraAbstract:Multi-Access Edge Computing (MEC) is one of the prominent 5G concepts that will allow service requirements that were not feasible so far due to the high communications latency and rigidness of cellular networks. The ETSI and the 3GPP are working towards the standardization of MEC applications integration in 5G networks, and how to route user traffic to a Local Area Data Network where local applications are deployed. Nevertheless, there are no practical implementations that facilitate the dynamic relocation of applications from the core to a MEC host, or from a MEC host to another without interruption and transparently to User Equipment (UE). Furthermore, the MEC concept can also be included in a 4G network to provide new advanced services with existing infrastructures. In this paper we propose to use Software Defined Networking (SDN) to create a new instance of the IP Anchor Point to dynamically redirect the UE traffic to a new physical location (e.g. an edge infrastructure) while maintaining session and service continuity. We also present a novel, completely distributed approach based on SDN to maintain the previous context of the connection in the new instance of the IP Anchor Point, and we analyze the performance of this mechanism in comparison to other possible alternatives to keep the session state. This approach can be used to implement edge services in a 4G or 5G network.
Yanghee Choi - One of the best experts on this subject based on the ideXlab platform.
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Comparison of IPv6 mobility management schemes: a focus on network mobility
2015Co-Authors: Hosik Cho, Taekyoung Kwon, Yanghee ChoiAbstract:Abstract- In this paper, we compare IPv6 mobility management schemes that support network mobility. A few schemes have been proposed to support network mobility considering the mobility of an entire network as a single unit. The mobile network includes one or more mobile routers (MRs), which connect it to the global Internet. NEMO basic support protocol (NBSP) is based on mobile IPv6 with prefix registration. Hierarchical mobile IPv6 (HMIPv6) introduces the mobility Anchor Point (MAP) that handles intra-domain handoffs locally. HMIPv6 can be extended to support network mobility by collocating mobility Anchor Point (MAP) and MR. Location independent network for IPv6 (LIN6) solves the triangular routing problem by introducing the concept of “mapping agent (MA), ” which manages the current location of the mobile network. NBSP and HMIPv6 basically follow mobile IPv6 protocol and therefore the data packets from correspondent hosts are forwarded to the mobile node (MN) via its home agent. LIN6 forwards the data packets directly to the MN without visiting the home agent at the cost of signaling for location resolution. We carry out analysis to compare the above three schemes in terms of packet transfer delay, signaling cost, and response time 1
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A performance comparison of mobility Anchor Point selection schemes in Hierarchical Mobile IPv6 networks
Computer Networks, 2007Co-Authors: Sangheon Pack, Taekyoung Kwon, Yanghee ChoiAbstract:Hierarchical Mobile IPv6 (HMIPv6) introduces a mobility Anchor Point (MAP) that localizes the signaling traffic and hence reduces the handoff latency. In addition to processing binding update messages from mobile nodes (MNs) on behalf of MNs' home agents (HAs), the MAP performs data traffic tunneling destined to or originated from MNs, both of which will burden the MAP substantially as the network size grows. To provide scalable and robust mobile Internet services to a large number of visiting MNs, multiple MAPs will be deployed. In such an environment, how to select an appropriate MAP has a vital effect on the overall network performance. In this paper, we choose four MAP selection schemes: the furthest MAP selection scheme, the nearest MAP selection scheme, the mobility-based MAP selection scheme, and the adaptive MAP selection scheme. Then, we compare their performances quantitatively in terms of signaling overhead and load balancing. It can be shown that the dynamic schemes (i.e., the mobility-based and the adaptive MAP selection schemes) are better than the static schemes (i.e., the furthest and the nearest MAP selection schemes), since the dynamic schemes can select the serving MAP depending on the MN's characteristics, e.g., mobility and session activity. In addition, the adaptive MAP selection scheme achieves low implementation overhead and better load balancing compared with the mobility-based MAP selection scheme.
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An adaptive mobility Anchor Point selection scheme in Hierarchical Mobile IPv6 networks
Computer Communications, 2006Co-Authors: Sangheon Pack, Minji Nam, Taekyoung Kwon, Yanghee ChoiAbstract:In Hierarchical Mobile IPv6 (HMIPv6) networks, the mobility Anchor Point (MAP) is introduced to localize binding update messages destined to the home agent. In a large-scale wireless/mobile network, multiple MAPs may be deployed in order to provide more scalable and robust mobile services. In this case, it is important for a mobile node (MN) to select the most appropriate MAP among them. In this paper, we propose an adaptive MAP selection scheme for HMIPv6 networks. In the adaptive MAP selection scheme, an MN first estimates its session-to-mobility ratio (SMR). Then, based on its SMR, the MN chooses a MAP that minimizes the total cost, consisting of the binding update cost and packet delivery cost. In addition, the MN calculates two threshold SMR values, which adaptively trigger a new MAP selection procedure. If the estimated SMR is larger (or smaller) than the upper (or lower) threshold SMR value, the MN recalculates the total cost and re-selects a MAP that minimizes the total cost. Simulation results indicate that the adaptive MAP selection scheme achieves a lower total cost and a better load balancing than the previous schemes.
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a mobility based load control scheme at mobility Anchor Point in hierarchical mobile ipv6 networks
Global Communications Conference, 2004Co-Authors: Sangheon Pack, Taekyoung Kwon, Yanghee ChoiAbstract:In this paper, we propose a mobility-based load control scheme, which consists of two sub-algorithms: (1) a threshold-based admission control algorithm; and (2) a session-to-mobility ratio (SMR) based replacement algorithm. Here the SMR is defined as a ratio of the session arrival rate to the handoff rate. When the number of mobile nodes (MNs) at a mobile Anchor Point (MAP) reaches to the full capacity, the MAP replaces an existing MN at the MAP, whose SMR is high, with an MN that just requests a binding update. The replaced MN is redirected to its home agent. We analyze the proposed load control scheme using the Markov chain model in terms of the new MN blocking probability and the ongoing MN dropping probability. By combining the threshold-based admission control with the SMR-based replacement, the above probabilities are lowered significantly compared to the threshold-based admission control alone.
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a comparative study of mobility Anchor Point selection schemes in hierarchical mobile ipv6 networks
Mobility Management and Wireless Access, 2004Co-Authors: Sangheon Pack, Taekyoug Kwon, Yanghee ChoiAbstract:In Hierarchical Mobile IPv6 networks, how an mobile node select an appropriate mobility Anchor Point (MAP) has a vital effect on the overall network performance. In this paper, we evaluate the performances of four MAP selection schemes: the furthest MAP selection scheme, the nearest MAP selection scheme, the mobility-based MAP selection scheme, and the adaptive MAP selection scheme. The dynamic schemes (i.e., the mobility-based and the adaptive MAP selection schemes) achieve more desirable performances than the static schemes (i.e., the furthest and the nearest MAP selection schemes), since the dynamic schemes consider mobility of MNs. Also, the dynamic schemes can achieve load balancing among MAPs, where the adaptive MAP selection is better than the mobility-based MAP selection scheme.