NetCube: a comprehensive network traffic analysis model based on multidimensional OLAP data cube

Network traffic monitoring and analysis are essential for effective network operation and resource management. In particular, multidimensional analysis for long‐term traffic data is necessary for comprehensive understanding of the traffic trend and effective quality‐of‐service provision considering the extremely dynamic behavior of the current Internet, where various types of traffic occur from high‐speed network links and greatly increasing number of applications. However, only limited analysis results are provided, as the existing network traffic analysis tools and systems are developed and deployed focusing on their own specialized analysis purposes. Consequently, it is difficult to understand the network comprehensively and deeply, which increases the necessity for multilateral analysis of long‐term traffic data. In this paper, we propose a novel traffic analysis model for large volumes of Internet traffic accumulated over a long period of time. The NetCube, the proposed network traffic analysis model using online analytical processing (OLAP) on a multidimensional data cube, provides an easy and fast way to construct a multidimensional traffic analysis system for comprehensive and detailed analysis of long‐term traffic data by utilizing simple OLAP operations and powerful data‐mining techniques on various abstraction levels of traffic data to complete the analysis purpose. We validate the feasibility and applicability of the proposed NetCube traffic analysis model by implementing a traffic analysis system and applying it to our campus network. Copyright © 2012 John Wiley & Sons, Ltd.     

On using peer-to-peer communication in cellular wireless data networks

A recent class of approaches for enhancing the performance of cellular wireless data networks has focused on improving the underlying network model. It has been shown that using the peer-to-peer network model, a mode of communication typically seen in ad hoc wireless networks, can result in performance improvements such as increased data rate, reduced transmission power, better load balancing, and enhanced network coverage. However, the true impact of adopting the peer-to-peer network model in such an environment is yet to be fully understood. In this paper, we investigate the performance benefits and drawbacks of using the peer-to-peer network model for Internet access in cellular wireless data networks. We find that, although the peer-to-peer network model has significantly better spatial reuse characteristics, the improved spatial reuse does not translate into better throughput performance. Instead, we observe that using the peer-to-peer network model as-is might actually degrade the throughput performance of the network. We identify and discuss the reasons behind these observations. Using the insights gained through the performance evaluations, we then propose two categories of approaches to improve the performance of the peer-to-peer network model: approaches that leverage assistance from the base station and approaches that leverage the relaying capability of multihomed hosts. Through simulation results, we show that using the peer-to-peer network model in cellular wireless data networks is a promising approach when the network model is complemented with appropriate mechanisms.     

Enhancing quality of experience using peer‐to‐peer overlay on device‐to‐device communications

With the recent development of LTE‐A/5G technologies, data sharing among mobile devices offer an attractive opportunity to reduce Internet access. However, it requires smart strategies to share the data with low trade‐offs in time, cost, and energy. Several existing schemes offer a super‐peer‐based two‐tier model using a distributed hash table (DHT) organization for smart devices having device‐to‐device (D2D)/Bluetooth/WiFi capabilities. The primary focus of these schemes has been to reduce Internet usage by increased D2D content sharing. However, the real challenge is not in creating a two‐tier model, but evolving an efficient overlay that offers enhanced opportunities for D2D content sharing over the existing model. In this paper, we formulated a P‐median‐based selection of tier‐1 devices in a distribution network and solved it using the Lagrangian relaxation method. The tier‐2 devices become clients seeking content sharing services from tier‐1 devices. A strong motivation in this work is to raise a user's perception of the grade of service known as quality of experience (QoE). We analyzed the challenge for QoE assessment in resource‐constrained smartphones under the proposed model of enhanced D2D communication. Our focus is to establish a framework to evaluate QoE for applications and services over LTE‐A/5G networks with an improved D2D communication level. The simulation and the experimental results validate the claim that substantial improvements in QoE are possible with the proposed mathematical model for selecting and placing tier‐1 mobile devices and maintaining a DHT for D2D communication.     

A Statistic and Analysis of Access Pattern for Online VoD Multimedia

The generally accepted that Zipf-Distribution is a convinced access pattern for text-based Web. However, with the dramatic increasement of VoD media traffic on the Internet such as Flash P2P, the inconsistency between the access patterns of media objects and the Zipf model has been researched by many scholars. In this paper, we have studied a large variety of media work-loads collected from both browser and server sides in Adobe Flash P2P systems which applied in Youku, Youtube, etc. Through extensive analysis and modeling. And found the object reference ranks of all these workloads follow the logistic (LOG) distribution despite their different media systems and delivery methods by extensive analysis and modeling. This mean it does not follow long tail effect; Furthermore, we have constructed mathematical models which can applied in access pattern in FlashP2P traffic. By analyzing the model of media traffic access, it is possible to better describe the user’s access mode. Meantime, it is very suitable for the configuration and allocation of network resources which can be used more efficiently.

     

A self‐adaptive load‐dispatching control framework for device data accessing in IoT‐based systems

The Internet of things (IoT) information system plays important roles in disposing of huge volumes of real‐time service requests from heterogeneous devices, targeting for different complex application requirements. Load‐dispatching control (LDC) is a key problem to be solved for devices accessing concurrently in cluster systems. Self‐adaptive LDC optimizes the resource allocation to ensure no overloading node, thus, improving the performance of IoT systems. This paper focuses on adaptive dispatching control problem in IoT information system. First, a device data access platform is proposed for reducing the load imbalance and improving the efficiency of data processing. Then, we propose a processing capability prediction model to evaluate the system performance. On the basis of the model, we present a practical self‐adaptive LDC framework with a self‐adaptive control strategy and a load dispatching method. Finally, a case study is given to verify the framework and the control strategy. Experimental results show that the proposed strategy can meet the requirements of dynamic load balancing with the ability to avoid the load imbalance problem, and the LDC‐based device access platform can process data accessing effectively and ubiquitously.     

LPPA: Lightweight privacy‐preservation access authentication scheme for massive devices in fifth Generation (5G) cellular networks

Because of the requirements of stringent latency, high‐connection density, and massive devices concurrent connection, the design of the security and efficient access authentication for massive devices is the key point to guarantee the application security under the future fifth Generation (5G) systems. The current access authentication mechanism proposed by 3rd Generation Partnership Project (3GPP) requires each device to execute the full access authentication process, which can not only incur a lot of protocol attacks but also result in signaling congestion on key nodes in 5G core networks when sea of devices concurrently request to access into the networks. In this paper, we design an efficient and secure privacy‐preservation access authentication scheme for massive devices in 5G wireless networks based on aggregation message authentication code (AMAC) technique. Our proposed scheme can accomplish the access authentication between massive devices and the network at the same time negotiate a distinct secret key between each device and the network. In addition, our proposed scheme can withstand a lot of protocol attacks including interior forgery attacks and DoS attacks and achieve identity privacy protection and group member update without sacrificing the efficiency. The Burrows Abadi Needham (BAN) logic and the formal verification tool: Automated Validation of Internet Security Protocols and Applications (AVISPA) and Security Protocol ANimator for AVISPA (SPAN) are employed to demonstrate the security of our proposed scheme.     

Real-time call admission control for packet-switched networking by cellular neural networks

In this paper, novel call admission control (CAC) algorithms are developed based on cellular neural networks. These algorithms can achieve high network utilization by performing CAC in real-time, which is imperative in supporting quality of service (QoS) communication over packet-switched networks. The proposed solutions are of basic significance in access technology where a subscriber population (connected to the Internet via an access module) needs to receive services. In this case, QoS can only be preserved by admitting those user configurations which will not overload the access module. The paper treats CAC as a set separation problem where the separation surface is approximated based on a training set. This casts CAC as an image processing task in which a complex admission pattern is to be recognized from a couple of initial points belonging to the training set. Since CNNs can implement any propagation models to explore complex patterns, CAC can then be carried out by a CNN. The major challenge is to find the proper template matrix which yields high network utilization. On the other hand, the proposed method is also capable of handling three-dimensional separation surfaces, as in a typical access scenario there are three traffic classes (e.g., two type of Internet access and one voice over asymmetric digital subscriber line.     

Optimal resource allocation and adaptive call admission control for voice/data integrated cellular networks

Resource allocation and call admission control (CAC) are key management functions in future cellular networks, in order to provide multimedia applications to mobiles users with quality of service (QoS) guarantees and efficient resource utilization. In this paper, we propose and analyze a priority based resource sharing scheme for voice/data integrated cellular networks. The unique features of the proposed scheme are that 1) the maximum resource utilization can be achieved, since all the leftover capacity after serving the high priority voice traffic can be utilized by the data traffic; 2) a Markovian model for the proposed scheme is established, which takes account of the complex interaction of voice and data traffic sharing the total resources; 3) optimal CAC parameters for both voice and data calls are determined, from the perspective of minimizing resource requirement and maximizing new call admission rate, respectively; 4) load adaption and bandwidth allocation adjustment policies are proposed for adaptive CAC to cope with traffic load variations in a wireless mobile environment. Numerical results demonstrate that the proposed CAC scheme is able to simultaneously provide satisfactory QoS to both voice and data users and maintain a relatively high resource utilization in a dynamic traffic load environment. The recent measurement-based modeling shows that the Internet data file size follows a lognormal distribution, instead of the exponential distribution used in our analysis. We use computer simulations to demonstrate that the impact of the lognormal distribution can be compensated for by conservatively applying the Markovian analysis results.     

A congestion reduction mechanism using D2D cooperative relay for M2M communication in the LTE‐A cellular network

The Long Term Evolution‐advanced cellular network is designed for human‐to‐human communication. When a large number of machine‐to‐machine (M2M) devices are trying to access the network simultaneously, it leads to a low random access (RA) successful rate and high congestion problem, which may cause the waste of radio resources, packet loss, latency, extra power consumption, and the worst, M2M service error. There is an urge to propose an efficient method for M2M communication on the LTE‐A network to resolve the congestion problem. In this paper, we propose a congestion reduction mechanism, which can analyze and model the RA procedure on the Long Term Evolution‐advanced network, to find out the collapse point in the RA procedure and then design a scheme named device‐to‐device cooperative relay scheme to relieve the congestion problem. Meanwhile, this work also adds a relay access barring algorithm to improve performance and an RA resource separation mechanism for human‐to‐human communication. The proposed method can effectively reduce the network congestion problem. Simulation results show that the network throughput and the congestion can be significantly improved using the proposed mechanism. Copyright © 2016 John Wiley & Sons, Ltd.     

On the complexity of Internet traffic dynamics on its topology

Most studies of Internet traffic rely on observations from a single link. The corresponding traffic dynamics has been studied for more than a decade and is well understood. The study of how traffic on the Internet topology, on the other hand, is poorly understood and has been largely limited to the distribution of traffic among source-destination pairs inside the studied network, also called the traffic matrix. In this paper, we make a first step towards understanding the way traffic gets distributed onto the whole topology of the Internet. For this, we rely on the traffic seen by a transit network, for a period of more than a week. As we are still at the stage of understanding the topological traffic distribution, we do not try to model the traffic dynamics. Rather we concentrate on understanding the complexity of describing the traffic observed by a transit network, how it maps onto the AS-level topology of the Internet and how it changes over time. For this, we rely on well-known tools of multi-variate analysis and multi-resolution analysis. Our first observation is that the structure of the Internet topology highly impacts the traffic distribution. Second, our attempts at compressing the traffic on the topology through dimension reduction suggests two options for traffic modeling: (1) to ignore links on the topology for which we do not see much traffic, or (2) to ignore time scales smaller than a few hours. In either case, important properties of the traffic might be lost, so might not be an option to build realistic models of Internet traffic. Realistic models of Internet traffic on the topology are not out of reach though. In this paper, we identify two properties such models should have: (1) use a compact representation of the dependencies of the traffic on the topology, and (2) be able to capture the complex multi-scale nature of traffic dynamics on different types of links.     

Efficient device‐to‐device discovery and access procedure for 5G cellular network

A large number of new data‐consuming applications are emerging, and many of them involve mobile users. In the next generation of wireless communication systems, device‐to‐device (D2D) communication is introduced as a new paradigm to offload the increasing traffic to the user equipment. Before the traffic transmission, D2D discovery and access procedure is the first important step which needs to be completed. In this paper, our goal is to design a device discovery and access scheme for the fifth generation cellular networks. We first present two types of device discovery and access procedures. Then we provide performance analysis based on the Markov process model. In addition, we present numerical simulation on the Vienna Matlab platform. The simulation results demonstrate the viability of the proposed scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

Performance analysis of cellular mobile communication systems fordata transmission

Buffers are used to overcome the data losses due to the interruption of data transmission when a mobile station is handed over in a cellular network. Data traffic from a wireline network to its mobile data terminal, such as access to large commercial databases or data transmission from a main computer to its remote mobile terminal, is studied. Compound Poisson (CP) is used to approximate the arrival process of the data traffic, and a modulated D (MD) distribution is used to approximate the service and handover process. The performance of the queueing model CP/MD/1/N is analyzed. Probability generating functions and characteristic functions are used to evaluate the mean queue length and the mean burst delay for an infinite buffer system and the overflow probabilities versus the buffer size for a finite buffer system. A method is presented to find the probability transition matrix entries by recursively taking derivatives of the probability generating function of the number of the characters arriving during the service-time. The queue length distributions for a finite buffer, both at departure instants and at arbitrary time instants are derived. Comparison with simulation indicates that the model is accurate. The numerical results of the model confirm the effectiveness of the scheme     

CASA‐IoT: Scalable and context‐aware IoT access control supporting multiple users

The Internet of Things (IoT) supports many users and context‐aware applications controlling heterogeneous IoT devices. This differs from traditional networks, in which a single entity manages each device. Thus, new access control models must be created in order to support more responsive, scalable, secure, and autonomous management. This article presents an attribute‐based access control model, which applies conflict resolution and access delegation in a multiuser and multiapplication environment. With scalability in mind, we propose the caching of access permissions, as well as a split policy processing model in which the devices with enough computational power perform part of the processing. The proposed model was implemented as part of the ManIoT architecture an d evaluated in experiments on a testbed to demonstrate its efficiency. Results show that our model accelerates the processing of access management policies from 51% by up to 79%.     

Performance evaluation of a priority‐based resource allocation scheme for multiclass services in IoT

Recently, the deployment of novel smart network concepts, such as the Internet of things (IoT) or machine‐to‐machine communication, has gained more attention owing to its role in providing communication among various smart devices. The IoT involves a set of IoT devices (IoTDs) such as actuators and sensors that communicate with IoT applications via IoT gateways without human intervention. The IoTDs have different traffic types with various delay requirements, and we can classify them into two main groups: critical and massive IoTDs. The fundamental promising technology in the IoT is the advanced long‐term evolution (LTE‐A). In the future, the number of IoTDs attempting to access an LTE‐A network in a short period will increase rapidly and, thus, significantly reduce the performance of the LTE‐A network and affect the QoS required by variant IoT traffic. Therefore, efficient resource allocation is required. In this paper, we propose a priority‐based allocation scheme for multiclass service in IoT to efficiently share resources between critical and massive IoTD traffic based on their specific characteristics while protecting the critical IoTDs, which have a higher priority over the massive IoTDs. The performance of the proposed scheme is analyzed using the Geo/G/1 queuing system focusing on QoS guarantees and resource utilization of both critical and massive IoTDs. The distribution of service time of the proposed system is determined and, thus, the average waiting and service times are derived. The results indicate that the performance of the massive IoTDs depends on the data traffic characteristics of the critical IoTDs. Furthermore, the results emphasize the importance of the system delay analysis and demonstrate its effects on IoT configurations.     

Optimal dynamic transport selection for wireless portable devices

Recent technological advances in mobile computing and wireless communication have made portable devices, such as PDA, laptops, and wireless modems to be very compact and affordable. On the other hand, wireless networks have gained such wide popularity that new network infrastructure is continually introduced. It is thus likely that many of the future portable devices will be equipped with multiple wireless modems such as Bluetooth and 802.11 WLAN, in order to increase device inter‐operability. The availability of multiple modems can leverage the performance of the communication traffic generated by the applications, for example Internet access. We envision a tool for managing the device connection through these modems. At the core of this tool is an optimization engine that splits packet traffic across a subset of the available transports so that user's performance metrics are maximized. This paper describes a mathematical model for such an optimization problem considering its applicability to small portable devices. Relevant quality of service (QoS) parameters such as bandwidth, average delay, and energy consumption are covered in the model. The mathematical formulation is validated using a simulated environment. The experimental results have demonstrated the effectiveness of our model and captured the inter‐relationship among the quality parameters. Copyright © 2006 John Wiley & Sons, Ltd.     

A new traffic model for backbone networks and its application to performance analysis

In this paper, we present a new traffic model constructed from a random number of shifting level processes (SLP) aggregated over time, in which the lengths of the active periods of the SLP are of Pareto or truncated Pareto distribution. For both cases, the model has been proved to be asymptotically second‐order self‐similar. However, based on extensive traffic data we collected from a backbone network, we find that the active periods of the constructing SLPs can be approximated better by a truncated Pareto distribution, instead of the Pareto distribution as assumed in existing traffic model constructions. The queueing problem of a single server fed with a traffic described by the model is equivalently converted to a problem with a traffic described by Norros' model. For the tail probability of the queue length distribution, an approximate expression and upper bound have been found in terms of large deviation estimates and are mathematically more tractable than existing results. The effectiveness of the traffic model and performance results are demonstrated by our simulations and experimental studies on a backbone network. Copyright © 2007 John Wiley & Sons, Ltd.     

User behavior modeling of voice communications: an empirical study

In this study, analysis and modeling of arrival and service processes are presented in a comprehensive fashion in order to determine statistical properties of voice traffic from end‐user perspective in accordance with the queueing theory. For the first time in the literature, we introduce a user centric approach and examine these services considering both flow directions of voice traffic, the uplink and the downlink as opposed to existing studies with the network centric approach. In our study, we use experimental data composed of actual phone calls collected from 2G/3G networks. To achieve this, we designed and implemented a data collection system for mobile users and compared the results by using data from an operational cellular network. In order to determine the time correlation of voice calls, Hurst parameter estimation methods are used. On the basis of the outcomes, independency of call arrivals is shown. Additionally, it is shown that calls acquired from user and network centric approaches are both Poisson distributed. Next, looking at the problem from service process perspective, thorough analyses are performed to determine mathematical models that can best characterize call holding times. Maximum likelihood estimation and expectation maximization algorithm are used, and it is shown that the optimum mathematical model for the characterization of call holding times is the lognormal distribution family. Copyright © 2014 John Wiley & Sons, Ltd.     

Packet CDMA versus dynamic TDMA for multiple access in anintegrated voice/data PCN

A comparative evaluation of dynamic time-division multiple access (TDMA) and spread-spectrum packet code-division multiple access (CDMA) approaches to multiple access in an integrated voice/data personal communications network (PCN) environment are presented. After briefly outlining a cellular packet-switching architecture for voice/data PCN systems, dynamic TDMA and packet CDMA protocols appropriate for such traffic scenarios are described. Simulation-based network models which have been developed for performance evaluation of these competing access techniques are then outlined. These models are exercised with example integrated voice/data traffic models to obtain comparative system performance measures such as channel utilization, voice blocking probability, and data delay. Operating points based on typical performance constraints such as voice blocking probability 0.01 (for TDMA), voice packet loss rate 10^-3 (for CDMA), and data delay 250 ms are obtained, and results are presented     

ECDGP: extended cluster‐based data gathering protocol for vehicular networks

An important application in wireless networks is data collection. It aims to gather and deliver specific data for concerned authorities. Many researchers invest in vehicular ad hoc networks for that purpose to acquire data from different sources on the roads as from its vicinity. A vehicle is considered as a mobile data collector, it gathers real‐time or delay‐tolerant data such as road traffic, environmental information, and event advertisements. In a previous work, we have proposed a novel clustered data gathering protocol (CDGP) for vehicular ad hoc network, which improves the collection performance by implementing a new space division multiple access technique called dynamic space division multiple access and a retransmission mechanism in case of errors. However, CDGP supports only delay‐tolerant data as it does not use any aggregation technique. In this paper, we propose an enhancement of this protocol by extending it to support: (i) both real‐time and delay‐tolerant applications; (ii) multiple types of data; and (iii) aggregation of collected data prior to sending them to the initiator. We present the plausible analytical complexity of the extended CDGP, as we illustrate the superiority of its performance throughout the results obtained from simulation experiments, using a Freeway mobility model. Copyright © 2015 John Wiley & Sons, Ltd.     

Fair optimization of mesh‐connected WLAN hotspots

In Wireless mesh networks mesh access points (MAPs) forward traffic wirelessly towards users or Internet gateways. A user device usually connects to the MAP with the strongest signal, as such MAP should guarantee the best quality of service. However, this connection policy may lead to: (i) unfairness towards users that are distant from gateways; (ii) uneven distribution of users to MAPs; and (iii) inefficient use of network paths. We present a new model and solution approach to the problem of assigning users to MAPs and routing the data within the mesh network with the objective of providing max–min fair throughput. The problem is formulated as a mixed‐integer linear programming problem (MILP). Because of the inherent complexity of the problem, real size instances cannot be solved to optimality within the time limits for online optimization. Therefore, we propose an original heuristic solution algorithm for the resulting MILP. Both numerical comparisons and network simulations demonstrate the effectiveness of the proposed heuristic. For random networks, the heuristic achieves 98% of the optimal solution. Network simulations show that in medium‐sized networks, the number of users with at least 1Mbit/s minimum end‐to‐end rate increases by 550% when compared with the classical signal‐strength based association. Copyright © 2013 John Wiley & Sons, Ltd.