Traffic forecasting plays an important role in improving network quality and energy saving of mobile networks. In 5G, traffic forecasting directly influences the self-organizing network (SON) in managing and controlling the network effectively. Especially, long-term traffic forecasting can provide a detailed pattern of future traffic, besides permitting more time for planning and optimizing. Most of the traffic forecasting models used the history of traffic, while the utilization of another network KPIs (key performance indicators) for traffic forecasting is limited. Therefore, the authors propose here a practical platform and process for traffic forecasting, based on big data, machine-learning (ML), and network KPIs that are flexible to forecast accurately different statistical traffic characteristics of different types of cells (GSM, 3G, 4G) for both long- and short-term forecasting. The performance of the proposed model was evaluated by applying it to a real dataset that collected KPIs of more than 6000 cells of a real network during the years, 2016 and 2017.

Virtualizing the EPC (Evolved Packet Core) in modern carrier-grade networks provides more flexible and reliable network services by decoupling dependence on the hardware. Hy- pervisor and container are two popular virtualization techniques nowadays to enable virtualization of EPC. In this paper, we compared the Open5GCore, a 5G EPC prototype, over KVM and Docker, which are representatives of the hypervisor and container techniques. Moreover, to verify how each supports new services for Internet of Things (IoT) and Machine-to-Machine (M2M) communications, we also analyze the performance of two systems with the IoT and M2M traffic generated by Open5GMTC, a prototype tool for IoT/M2M platforms.

One of the most important technologies for future 5G networks is to utilize Network Function Virtualization (NFV) to virtualize the network components. NFV provides flexibility, short time to market, and low cost solution to build network services, which are important features of 5G networks. Although the idea of virtualization is just being applied to cellular networks, it has been used in the community of cloud computing. There are two main virtualization techniques, hypervisor and container. In this paper, we present our practical experience of virtualizing Open5GCore, a commercial product of SDN‐enabled Evolved Packet Core (EPC), over hypervisor and container. In addition to describing how to virtualize Open5GCore, we also present the experimental performance evaluation of the systems. Finally, some important lessons learned are provided.

In this paper, we present a systemic approach to provide deterministic delay guarantee for dynamic service chaining in software defined networking (SDN). The delay performance of service chaining in SDN is affected by signaling message exchange in control plane and packet transmissions in data plane, respectively. First, we develop an analytical method to characterize the delay performance of control plane when handling traffic with different priorities according to network calculus (NC) and queuing theory. Second, taking into account the estimated delay in control plane, we propose a novel service traversal mechanism to calculate the optimal traversal path for the service chain. We demonstrate that NC delay analysis can provide deterministic quality of service (QoS)-guaranteed service chaining for any specified delay requirements, whereas theoretical queueing delay analysis can only provide statistical QoS guarantee. In summary, the proposed NC delay analysis can help to understand the network design for a future delay sensitive Internet in which deterministic latency must be guaranteed.

Advanced vehicle safety is a recently emerging issue, appealed from the rapidly explosive population of car owners. Increasing driver assistance systems have been designed for warning drivers of what should be noticed by analyzing surrounding environments with sensors and/or cameras. As one of the hazard road conditions, road bumps not only damage vehicles but also cause serious danger, especially at night or under poor lighting conditions. In this paper we propose a vision-based road bump detection system using a front-mounted car camcorder, which tends to be widespread deployed. First, the input video is transformed into a time-sliced image, which is a condensed video representation. Consequently, we estimate the vertical motion of the vehicle based on the time-sliced image and infer the existence of road bumps. Once a bump is detected, the location fix obtained from GPS is reported to a central server, so that the other vehicles can receive warnings when approaching the detected bumpy regions. Encouraging experimental results show that the proposed system can detect road bumps efficiently and effectively. It can be expected that traffic security will be significantly promoted through the mutually beneficial mechanism that a driver who is willing to report the bumps he/she meets can receive warnings issued from others as well.

Advertisements and coupon forwarding among mobile devices and social platforms become significant in recent years. However, when users are in the crowded places where the network connection is unstable such as shopping malls, forwarding of advertisements to target users in limited time is challenge. Thus, we propose an interest-aware opportunistic advertising by mining social and consuming information system (ISC) and algorithm. In ISC system, we combine social relationship and consuming information to find out the consumers who have similar interest. ISC algorithm adopts the result of ISC system to reduce the delay of broadcasting advertisement and increase the advertisement effect. We also implement and evaluate the performance of ISC system and algorithm on mobile devices and the ONE simulator. Our experiment results show that ISC algorithm is cost effective and intensively magnify the advertising effeteness with many customers under uncertain network and time-limited environments.

For security concerns, a security traversal service can route data flows through a sequences of security devices (middleboxes). In this paper, we identify the problem of delay guarantee in security traversal and propose a scheme to dynamically change the security traversal path. To provide deterministic delay guarantee with minimum virtual machine (VM) and transmission cost, we model this security traversal path determination as a constrained shortest path problem (CSP) and propose an optimal security traversal with middlebox addition (OSTMA) mechanism. Besides, we implement the proposed OSTMA mechanism in an OpenFlow network by designing a centralized security traversal controller to dynamically monitor the network condition information and reconfigure the security traversal path. Our experimental results show that the proposed dynamic security traversal scheme can still achieve delay requirements for network topology changes and burst traffic.

Mobile Augmented Reality (MAR) is generally defined as the service that is capable of enhancing the real-world camera views of a smartphone with extra information on top of the screen. Thus, MAR has triggered strong interests in mobile e-commerce, location-based service, etc. However, MAR is usually constrained by the local storage and computing power of the device as well as the latency and bandwidth of the underlying wireless channel. The computation demand is high because a targeted object needs to be compared to lots of images in the database. The communication demand is high because potential objects need to be continuously transmitted to the server and the augmented information needs to be downloaded from the server. This paper investigates the Local Cache Management (LCM) problem to manage the computation and communication work of a mobile device and harmonize the local and remote workloads. We present strategies to pre-fetch higher-priority objects from the server and replace lower-priority objects in the local cache based on temporal and spatial access locality. We verify the effectiveness of our strategies in term of cache hit ratio, response latency, and remote requests via simulations.

ABSTRACT Recently, digital video broadcasting‐handheld (DVB‐H) and IP datacast over DVB‐H (DVB‐IPDC) have been developed to support broadcasting services. DVB‐H is designed to support digital video broadcast for handheld devices, whereas DVB‐IPDC can integrate with an IP‐relay network to complement the data loss problem in DVB‐H. Assuming that WiMAX networks are adopted to support DVB‐IPDC, this paper points out two critical problems: group packet loss (GPL) and broadcast data handover (BDH). GPL occurs when there is a burst of retransmission requests for the same pieces of data with high spatial or temporal correlation. BDH happens when some devices that made the above requests handover to new serving cells. To solve these problems, we propose lazy wait and group acknowledgement schemes to alleviate duplicate requests by exploiting their spatial and temporal correlations. This not only reduces the requests submitted by neighboring devices in both space and time domains but also avoids handovering devices from sending duplicate requests in new cells. Through mathematical analysis, we show how to adaptively adjust the timers of lazy wait and group acknowledgement based on channel quality. Simulation results prove that our schemes can efficiently reduce retransmission requests and retransmission packets, thus alleviating congestion in the IP‐relay network. Copyright © 2011 John Wiley & Sons, Ltd.

With the increasing popularity of cloud computing, Hadoop has become a widely used open source cloud computing framework for large scale data processing. However, few studies have been done to enhance data confidentiality of Hadoop against storage servers. In this paper, we address the data confidentiality issue by integrating hybrid encryption schemes and the Hadoop distributed file system (HDFS). We propose and implement two integrations, HDFS-RSA and HDFS-Pairing, as extensions of HDFS. Experiments are conducted to demonstrate the performance overhead of HDFS-RSA and HDFS-Pairing. Our integrations provide alternatives toward achieving data confidentiality for Hadoop.

Erasure code based distributed storage systems provide data robustness by storing encoded-fragments over servers. To maintain data robustness, a repair mechanism recovers a storage system from server failures by repairing encoded-fragments. For decentralized erasure code based storage systems, we propose a decentralized repair mechanism. Our mechanism has the following features. Firstly, an encoded- fragment is replenished by a combination of a number u of encoded-fragments that are randomly chosen. Secondly, the number u depends on the number of the available encoded- fragments and is independent of the pattern of missing encoded-fragments. Thirdly, multiple encoded-fragments are simultaneously replenished in parallel. We measure the communication cost in terms of the number u of required network connections for replenishing an encoded-fragment. We then conducted a numerical analysis by using traces of real systems. We find that our requirement on u is smaller than that from existing methods. Both theoretical and numerical results show that our decentralized repair mechanism outperforms existing ones in terms of the communication cost under the same consideration of efficiency cost for storage.

The DVB-H standard has been defined to provide digital video broadcast to mobile handheld devices. However, without a request channel, a handheld device may encounter data loss and thus it requires an additional recovery architecture to relieve this problem. In this paper, we follow the DVB-IPDC standard and propose combining a DVB-H system with an IP- relay wireless network. A handheld device losing DVB-H data can thus request the relay network for retransmission. Under this architecture, we identify two critical issues, group packet loss (GPL) and broadcast data handover (BDH). The GPL problem occurs when there are bursty requests for retransmissions of the same data with high spatial and temporal locality, causing network congestion. The BDH problem occurs when these requesting devices move out of their current serving cells. In this paper, we propose a bulk request recovery (BRR) scheme to solve these problems by exploiting spatial and temporal locality of recovery requests. Our scheme can efficiently reduce duplicate requests and schedule retransmissions of lost packets, so both GPL and BDH problems are relieved. Simulations results are also presented to verify the effectiveness of our result.

WiFi networks have been deployed in many regions such as buildings and campuses to provide wireless Internet access. However, to support ubiquitous wireless service, one possibility is to integrate these narrow-range WiFi networks with a wide-range network such as WiMAX. Under this WiMAX-WiFi integrated network, how to conduct energy-efficient handovers is a critical issue. In this paper, we propose a handover scheme with geographic mobility awareness (HGMA) by considering the past handover patterns of mobile devices. HGMA can conserve the energy of handovering devices from three aspects. First, it prevents mobile devices from triggering unnecessary handovers by measuring their received signal strength and moving speeds. Second, it includes a handover candidate selection (HCS) method for mobile devices to intelligently select a subset ofWiFi access points or WiMAX relay stations to be scanned. Therefore, mobile devices can reduce their network scanning and thus save their energy. Third, HGMA prefers mobile devices staying in their original WiMAX or WiFi networks. This can prevent devices from consuming too much energy on interface switching. Simulation results show that HGMA can reduce about 69% and 30% of energy consumption on network scanning and interface switching, respectively, and with 16% to 64% more probabilities for mobile devices staying in WiFi networks.

This paper presents a novel data placement and retrieving scheme or real-time multimedia stream playback via a scalable storage system.The multimedia streams are contiguous data packets which may be representing video, audio, or other media be retrieved simultaneously from a storage system on a real-time and on-demand basis, The major challenge in implementing the system is the support of simultaneously retrieving a big number of streams from a large-capacity storage system.This bottleneck comes from the seeking delay caused by the random movement of disk head in the storage under multiple stream requests.The proposed scheme efftciently reduces the seeking time by a very simple placement method and a retrieval scheduler and, in the mean time, continuous playback of multiple real-time streams and a scalable storage capacity are both achieved.Performance valuation of the proposed scheme is provided through theoretical analysis and experimental measure.

Personal mobile equipments are often required to be simple, inexpensive, as well as powerful in the same time, for instance, a lightweight mobile terminal with multimedia on Internet. We refer to this equipment as Mobile Multimedia Terminal (MMT). This paper presents a protocol architecture supporting the multimedia access for MMT in a wireless WAN environment. To save the processing power, each MMT has a service agent located in a server connected to the mobile switching center. Based upon this model, a transport protocol and architecture for mobile multimedia communications is proposed. The proposed protocol is intended for the handover and real-time data transportation between MMT and the MMT agent. Architectural design of the MMT and its agent will also be described.