254 research outputs found
Principles of Modeling in Information Communication Systems and Networks
The authors present in this entry chapter the basic rubrics of models, modeling, and simulation, an un-
derstanding of which is indispensible for the comprehension of subsequent chapters of this text on the
all-important topic of modeling and simulation in Information Communication Systems and Networks
(ICSN). A good example is the case of analyzing simulation results of traffic models as a tool for investigat-
ing network behavioral pattarns as it affects the transmitted content (Atayero, et al., 2013). The various
classifications of models are discussed, for example classification based on the degree of semblance to
the original object (i.e. isomorphism). Various fundamental terminologies without the knowledge of which
the concepts and models and modeling cannot be properly understood are explained. Model stuctures
are highlighted and discussed. The methodological basis of formalizing complex system structures is
presented. The concept of componential approach to modeling is presented and the necessary stages of
mathematical model formation are examined and explained. The chapter concludes with a presentation
of the concept of simulation vis-à-vis information communication systems and networks
A Multi-channel Application Framework for Customer Care Service Using Best-First Search Technique
It has become imperative to find a solution to the dissatisfaction in response by mobile
service providers when interacting with their customer care centres. Problems faced with
Human to Human Interaction (H2H) between customer care centres and their customers
include delayed response time, inconsistent solutions to questions or enquires and lack of
dedicated access channels for interaction with customer care centres in some cases.
This paper presents a framework and development techniques for a multi-channel
application providing Human to System (H2S) interaction for customer care centre of a
mobile telecommunication provider. The proposed solution is called Interactive Customer
Service Agent (ICSA). Based on single-authoring, it will provide three media of interaction
with the customer care centre of a mobile telecommunication operator: voice, phone and
web browsing. A mathematical search technique called Best-First Search to generate
accurate results in a search environmen
Modeling of Packet Streaming Services in Information Communication Networks
Application of the term video streaming in contemporary usage denotes compression techniques and
data buffering, which can transmit video in real time over the network. There is currently a rapid growth
and development of technologies using wireless broadband technology as a transport, which is a seri-
ous alternative to cellular communication systems. Adverse effect of the aggressive environment used
in wireless networks transmission results in data packets undergoing serious distortions and often get-
ting lost in transit. All existing research in this area investigate the known types of errors separately. At
present there are no standard approaches to determining the effect of errors on transmission quality of
services. Besides, the spate in popularity of multimedia applications has led to the need for optimization
of bandwidth allocation and usage in telecommunication networks. Modern telecommunication networks
should by their definition be able to maintain the quality of different applications with different Quality
of Service (QoS) levels. QoS requirements are generally dependent on the parameters of network and
application layers of the OSI model. At the application layer QoS depends on factors such as resolution,
bit rate, frame rate, video type, audio codecs, and so on. At the network layer, distortions (such as delay,
jitter, packet loss, etc.) are introduced
A Soft Computing Approach to Dynamic Load Balancing in 3GPP LTE
A major objective of the 3GPP LTE standard is the provision of high-speed data services. These services must be guaranteed under varying radio propagation conditions, to stochastically distributed mobile users. A necessity for determining and regulating the traffic load of eNodeBs naturally ensues. Load balancing is a self-optimization operation of self-organizing networks (SON). It aims at ensuring an equitable distribution of users in the network. This translates into better user satisfaction and a more efficient use of network resources. Several methods for load balancing have been proposed. Most of the algorithms are based on hard (traditional) computing which does not utilize the tolerance for precision of load balancing. This paper proposes the use of soft computing, precisely adaptive Neuro-fuzzy inference system (ANFIS) model for dynamic QoS aware load balancing in 3GPP LTE. The use of ANFIS offers learning capability of neural network and knowledge representation of fuzzy logic for a load balancing solution that is cost effective and closer to human intuitio
Interworking Architectures in Heterogeneous Wireless Networks: An Algorithmic Overview
The scarce availability of spectrum and the proliferation of
smartphones, social networking applications, online gaming
etc., mobile network operators (MNOs) are faced with an
exponential growth in packet switched data requirements on
their networks. Haven invested in legacy systems (such as
HSPA, WCDMA, WiMAX, Cdma2000, LTE, etc.) that have
hitherto withstood the current and imminent data usage
demand, future and projected usage surpass the capabilities of the evolution of these individual technologies. Hence, a more critical, cost-effective and flexible approach to provide ubiquitous coverage for the user using available spectrum is of high demand. Heterogeneous Networks make use of these legacy systems by allowing users to connect to the best network available and most importantly seamlessly handover active sessions amidst them. This paper presents a survey of interworking architectures between IMT 2000 candidate networks that employ the use of IEFT protocols such as MIP, mSCTP, HIP, MOBIKE, IKEV2 and SIP etc. to bring about this much needed capacity
Adaptive Neuro-Fuzzy Inference System for Dynamic Load Balancing in 3GPP LTE
ANFIS is applicable in modeling of key parameters when investigating the performance and functionality of wireless networks. The need to save both capital and operational expenditure in the management of wireless networks cannot be over-emphasized. Automation of network operations is a veritable means of achieving the necessary reduction in CAPEX and OPEX. To this end, next generations networks such WiMAX and 3GPP LTE and LTE-Advanced provide support for self-optimization, self-configuration and self-healing to minimize human-to-system interaction and hence reap the attendant benefits of automation. One of the most important optimization tasks is load balancing as it affects network operation right from planning through the lifespan of the network. Several methods for load balancing have been proposed. While some of them have a very buoyant theoretical basis, they are not practically implementable at the current state of technology. Furthermore, most of the techniques proposed employ iterative algorithm, which in itself is not computationally efficient. This paper proposes the use of soft computing, precisely adaptive neuro-fuzzy inference system for dynamic QoS-aware load balancing in 3GPP LTE. Three key performance indicators (i.e. number of satisfied user, virtual load and fairness distribution index) are used to adjust hysteresis task of load balancing
ANFIS Modeling of Dynamic Load Balancing in LTE
Modelling of ill-defined or unpredictable systems can be very challenging. Most models have relied on
conventional mathematical models which does not adequately track some of the multifaceted challenges
of such a system. Load balancing, which is a self-optimization operation of Self-Organizing Networks
(SON), aims at ensuring an equitable distribution of users in the network. This translates into better user
satisfaction and a more efficient use of network resources. Several methods for load balancing have been
proposed. While some of them have a very buoyant theoretical basis, they are not practical. Furthermore,
most of the techniques proposed the use of an iterative algorithm, which in itself is not computationally
efficient as it does not take the unpredictable fluctuation of network load into consideration. This chapter
proposes the use of soft computing, precisely Adaptive Neuro-Fuzzy Inference System (ANFIS) model,
for dynamic QoS aware load balancing in 3GPP LTE. The use of ANFIS offers learning capability of
neural network and knowledge representation of fuzzy logic for a load balancing solution that is cost
effective and closer to human intuition. Three key load parameters (number of satisfied user in the net-
work, virtual load of the serving eNodeB, and the overall state of the target eNodeB) are used to adjust
the hysteresis value for load balancing
Applications of Soft Computing in Mobile and Wireless Communications
Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications
Simulation of the Effect of Data Exchange Mode Analysis on Network Throughput
Emergence of large scale specialized networks with a large number of computers
marked a new stage in network infrastructure development. In connection with the wide
variety of modern network equipment used for construction of large-scale networks and
increasing complexity of such networks and applications, a developer or system
administrator can no longer depend mainly on intuitive decisions. Optimum network configuration for realization of concrete tasks and effective deployment of applications in modern terms is not possible without conducting a proper research with the use of specialized simulation tools. Increase in bandwidth is followed by a commensurate increase
in the amount of traffic sent over the Internet. Optimizing the use and allocation of bandwidth continues to be an ongoing problem. We present a simulation model to resolve
the technological challenges of increasing the efficiency of data exchange in computer networks
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