# IEEE Transactions on Network and Service Management

View this topic in

# 760 resources related to IEEE Transactions on Network and Service Management

### Conferences related to IEEE Transactions on Network and Service Management

2019 IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

IEEE WoWMoM 2019 is soliciting original and previously unpublished papers addressing research challenges and advances in the areas of wireless, mobile, and multimedia networking as well as ubiquitous and pervasive systems.

2019 IEEE World Congress on Services (SERVICES)

The scope of the Congress will cover all aspects of innovative services computing and applications, current and emerging. It involves various systems and networking aspects, such as cloud, edge, and Internet-of-Things (IoT), as well as other research and technologies, such as intelligent computing, learning techniques, blockchain and big data, including quality factors, such as high performance, security, privacy, dependability, trustworthiness, and cost-effectiveness.

2018 10th International Conference on Communication Software and Networks (ICCSN)

2018 10th International Conference on Communication Software and Networks (ICCSN 2018) will be held during July 6-9, 2018 in Chengdu, China. ICCSN 2018 is sponsored by University of Electronic Science and Technology of China, co-sponsored by 54th Institute, CETC, China, Science and Technology on Communication Networks Laboratory, supported by Guangdong University of Technology, China and AET Journal.

2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)

We invite submissions of high quality papers describing fully developed results or on-going foundational and applied work on the following topics:Agent for e-Business TrackData and Big Data for e-Business TrackInternet of Things (IoT) and Edging/Fog Computing TrackMobile and Autonomous Computing TrackSecurity, Privacy, Trust, and Credit TrackService-Oriented and Cloud TrackSoftware Engineering for e-Business TrackEmerging Ecommerce Supporting Technologies (Blockchain / Nature Language Engineering / Smart Brokers) Track

2018 IEEE 18th International Conference on Communication Technology (ICCT)

ICCT 2018 will always keep promoting the information exchange on communication technology, which aims to promote international academic exchange and international cooperation, and provides an opportunity for researchers around the world to exchange ideas and latest research results, in both theory and application of communication technologies. Besides the technical sessions, there will be the invited sessions, tutorials, keynote addresses and exhibitions.

### Periodicals related to IEEE Transactions on Network and Service Management

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...

### Xplore Articles related to IEEE Transactions on Network and Service Management

IEEE Transactions on Network and Service Management, None

Edge computing is based on the philosophy that the data should be processed within the locality of its source. Edge computing is entering a new phase where it gains wide acceptance from both academia and the industry as the commercial deployments are starting. Edge of the network presents a very dynamic environment with many devices, intermittent traffic, high mobility of ...

IEEE Transactions on Network and Service Management, None

In data centers, a lot of cluster computing applications follow the coflow working pattern. That is, a collection of flows between two groups of machines is semantically related. On the other hand, network function virtualization (NFV) sufficiently improves the performance of data center networks. It, however, complicates the network environment by introducing many multi- function middleboxes each with multiple resources. ...

IEEE Transactions on Network and Service Management, None

The combination of network virtualization and software-defined networking (SDN) enables an infrastructure provider (InP) to create software-defined virtual networks (vSDNs) over a shared substrate network (SNT), for supporting new network services more timely and cost-effectively. Meanwhile, as both the services and traffic in the Internet are becoming more and more dynamic, how to properly maintain vSDNs in a dynamic network ...

IEEE Transactions on Network and Service Management, 2017

From Definition 2 in the above-named work, we have for a simple graph$G=(V,E)$, the following expression for the chromatic entropy$I_{C}(G)$of a graph:\begin{equation*} I_{C}\left ({G}\right) = \min _{\left \{{C_{i}}\right \}} - \sum _{i=1}^{N_{c}} \frac {|C_{i}|}{n} \log _{2} \frac {|C_{i}|}{n} \tag{1}\end{equation*}

IEEE Transactions on Network and Service Management, 2018

Group mobility in mobile networks is responsible for dynamic changes in user accesses to base stations, which eventually lead to degradation of network quality of service (QoS). In particular, the rapid movement of a dense group of users intensively accessing the network, such as passengers on a train passing through a densely populated area, significantly affects the perceived network QoS. ...

### Educational Resources on IEEE Transactions on Network and Service Management

#### IEEE-USA E-Books

• Edge computing is based on the philosophy that the data should be processed within the locality of its source. Edge computing is entering a new phase where it gains wide acceptance from both academia and the industry as the commercial deployments are starting. Edge of the network presents a very dynamic environment with many devices, intermittent traffic, high mobility of the end user, heterogeneous applications and their requirements. In this scene, scalable and efficient management &amp; orchestration remains to be a problem. We focus on the workload orchestration problem in which execution locations for incoming tasks from mobile devices are decided within an edge computing infrastructure, including the global cloud as well. Workload orchestration is an intrinsically hard, online problem. We employ a Fuzzy Logic based approach to solve this problem by capturing the intuition of a real world administrator to get an automated management system. Our approach takes into consideration the properties of the offloaded task as well as the current state of the computational and networking resources. Detailed set of experiments are designed with EdgeCloudSim to demonstrate the competitive performance of our approach for different service classes.

• In data centers, a lot of cluster computing applications follow the coflow working pattern. That is, a collection of flows between two groups of machines is semantically related. On the other hand, network function virtualization (NFV) sufficiently improves the performance of data center networks. It, however, complicates the network environment by introducing many multi- function middleboxes each with multiple resources. Coflows encounter extremely different processing delays under diverse network functions. Prior coflow scheduling schemes are insufficient to guarantee the coflow completion time (CCT) in the multi-resource environment. In this paper, we propose, model, and analyze the coflow scheduling problem in the multi-resource environment. We present a dedicated method, DRGC (Data Rate Guarantee for Coflow), to guarantee the data rate requirements of coflows in this situation. DRGC prioritizes the coflow scheduling sequence, assigns precise data rates for coflows, and deploys a packet scheduling algorithm at middleboxes to guarantee their transmissions. In our experiments, DRGC efficiently guarantees the completion times of coflows and supports 15% more workload, compared with other scheduling schemes.

• The combination of network virtualization and software-defined networking (SDN) enables an infrastructure provider (InP) to create software-defined virtual networks (vSDNs) over a shared substrate network (SNT), for supporting new network services more timely and cost-effectively. Meanwhile, as both the services and traffic in the Internet are becoming more and more dynamic, how to properly maintain vSDNs in a dynamic network environment exhibits increasing importance but still has not been fully explored. In this work, we conduct a study on how to realize proactive and hitless vSDN reconfiguration to balance the utilization of ternary content-addressable memory (TCAM) in a dynamic SNT. Specifically, we consider both algorithm design and system prototyping. From the algorithmic perspective, we try to solve the problems of “what to reconfigure" and “how to reconfigure". A selection algorithm is designed to proactively choose the virtual switches (vSWs) that should be migrated to other substrate switches (S-SWs) for balancing TCAM utilization, i.e., solving “what to reconfigure". Then, for the problem of “how to reconfigure", i.e., where to re-map the selected vSWs and the virtual links (VLs) connecting to them, we formulate a mixed integer linear programming (MILP) model to solve it exactly, and design two heuristics to improve time efficiency. Next, we move to the system part, implement the proposed algorithms in our protocol-oblivious forwarding (POF) enabled network virtualization hypervisor (NVH) system, and conduct experiments to demonstrate proactive and hitless vSDN reconfiguration. The experimental results indicate that our proposal does make vSDN reconfiguration transparent to the vSDNs’ virtual controllers (vCs) and proactive, and when reconfiguring a vSDN with live traffic, it achieves hitless operations without traffic disruption.

• From Definition 2 in the above-named work, we have for a simple graph$G=(V,E)$, the following expression for the chromatic entropy$I_{C}(G)$of a graph:\begin{equation*} I_{C}\left ({G}\right) = \min _{\left \{{C_{i}}\right \}} - \sum _{i=1}^{N_{c}} \frac {|C_{i}|}{n} \log _{2} \frac {|C_{i}|}{n} \tag{1}\end{equation*}

• Group mobility in mobile networks is responsible for dynamic changes in user accesses to base stations, which eventually lead to degradation of network quality of service (QoS). In particular, the rapid movement of a dense group of users intensively accessing the network, such as passengers on a train passing through a densely populated area, significantly affects the perceived network QoS. For better design and operation of mobile network facilities and functions in response to this issue, monitoring group mobility and modeling the access patterns in group mobility scenarios are essential. In this paper, we focus on fast and dense group mobility and mobile network signaling data (control-plane data), which contains information related to mobility and connectivity. Firstly, we develop a lightweight method of group mobility detection to extract train passengers from all users' signaling data without relying on precise location information about users, e.g., based on GPS. Secondly, based on the same signaling data and the results obtained by the detection method, we build connected/idle duration models for train users and non-train users. Finally, we leverage these models in mobile network simulations to assess the effectiveness of a dynamic base station switching/orientation scheme to mitigate QoS degradation with low power consumption in a group mobility scenario. The obtained models reveal that train users consume 3.5 times more resources than non-train users, which proves that group mobility has a significant effect on mobile networks. The simulation results show that the dynamic scheme of base station improves users' perceived throughput, latency and jitter with small amount of additional power consumption in case of a moderate number of train users, but its ineffectiveness with larger number of train users is also shown. This would suggest that group mobility detection and the obtained connection/idle duration models based solely on control-plane data analytics are usable and useful for the development of mobility-aware functions in base stations.

• Energy efficiency has recently become a major issue in large data centers due to financial and environmental concerns. This paper proposes an integrated energy-aware resource provisioning framework for cloud data centers. The proposed framework: i) predicts the number of virtual machine (VM) requests, to be arriving at cloud data centers in the near future, along with the amount of CPU and memory resources associated with each of these requests, ii) provides accurate estimations of the number of physical machines (PMs) that cloud data centers need in order to serve their clients, and iii) reduces energy consumption of cloud data centers by putting to sleep unneeded PMs. Our framework is evaluated using real Google traces collected over a 29-day period from a Google cluster containing over 12,500 PMs. These evaluations show that our proposed energy-aware resource provisioning framework makes substantial energy savings.

• When a link or node fails, flows are detoured around the failed portion, so the hop count of flows and the link load could change dramatically as a result of the failure. As real-time traffic such as video or voice increases on the Internet, ISPs are required to provide stable quality as well as connectivity at failures. For ISPs, how to effectively improve the stability of these qualities at failures with the minimum investment cost is an important issue, and they need to effectively select a limited number of locations to add link facilities. In this paper, efficient design algorithms to select the locations for adding link facilities are proposed and their effectiveness is evaluated using the actual backbone networks of 36 commercial ISPs.

• We propose an optimization model for designing multiple network functions virtualization (NFV)-based campus area networks (CANs). Organizations, such as universities and research institutions have their own campus information and communication technology equipment, but many would like to move this equipment to NFV and cloud data centers for improving reliability and resiliency. However, NFV-based CAN is not affordable for them, because costs are higher with a cloud. One solution is for multiple organizations to procure NFV and cloud data center resources together. By doing so, their individual costs of using these resources will be reduced. To make progress on this approach, there are planning issues to resolve when choosing optimal NFV and cloud data center locations. The proposed model minimizes the total network costs incurred by the organizations, including the wide area network cost and data synchronization costs for recovery from faults at data centers and the various subcampus network configurations of legacy CANs. The model is formulated and analyzed by using mixed integer linear programming. The effect of cost minimization is evaluated in a ladder network and an actual network, SINET5, and it is found that the costs can be reduced by up to 63%. The calculation times of this model under practical conditions are short and the model will be useful in practice. It is also shown that the cost of fault recovery can be suppressed. These results will encourage organizations to deploy NFV-based CANs.

• Many critical e-commerce and financial services are deployed on geo- distributed data centers for scalability and availability. Recent market surveys show that failure of a data center is inevitable resulting in a huge financial loss. Fault-tolerance in distributed data centers is typically handled by provisioning spare capacity to mask failure at a site. We argue that the operating cost and data replication cost (for data availability) must be considered in spare capacity provisioning along with minimizing the number of servers. Since the operating cost and client demand vary across space and time, we propose cost-aware capacity provisioning to minimize the total cost of ownership (TCO) for fault-tolerant data centers. We formulate the problem of spare capacity provisioning in fault-tolerant distributed data centers using mixed integer linear programming (MILP), with an objective of minimizing the TCO. The model accounts for heterogeneous client demand, data replication strategies (single and multiple site), variation in electricity price and carbon tax, and delay constraints while computing the spare capacity. Solving the MILP using real-world data, we observed a saving in the TCO to the tune of 35% compared to a model that minimizes the total number of servers and 43% compared to the model that minimizes the average response time. We demonstrate that our model is beneficial when the cost of electricity, carbon tax, and bandwidth vary significantly across the locations, which seems to be the problem for most of the operators.

• The memory Internet routers use to store paths to destinations is expensive, and must be continually upgraded in the face of steadily increasing routing table size. Unfortunately, routing protocols are not designed to gracefully handle cases where memory becomes full, which arises increasingly often due to misconfigurations and routing table growth. Hence router memory must typically be heavily overprovisioned by network operators, inflating operating costs and administrative effort. The research community has primarily focused on clean- slate solutions that cannot interoperate with the deployed base of protocols. This paper presents an incrementally-deployable Memory Management System (MMS) that reduces associated router state by up to 70%. The MMS coalesces prefixes to reduce memory consumption and can be deployed locally on each router or centrally on a route server. The system can operate transparently, without requiring changes in other ASes. Our memory manager can extend router lifetimes up to seven years, given current prefix growth trends.