Resilience in SDN control plane is a challenging goal when a single controller is employed. Thus, distributed controllers are deployed to realize a resilient and reliable software defined network. However, such a strategy can not succeed without an efficacious controller-switch assignment scheme. In addition to zero-day assignment, online re-assignment is crucial since due to network failures, the connections between controllers and switches may break off intermittently and impair the network operation. In this paper, we propose a reactive assignment model against network failures using integer linear programming based on load distribution of controllers. We augment our proposal with simulated annealing and random assignment approaches for switch, link and controller failures. The experimental results show that our model gives resilience against network failures and load-awareness is a effective strategy for controller assignment.

Future Internet is going to be shaped by networked multimedia services with exploding video traffic becoming the dominant payload. That evolution requires a remedial shift from the connection-oriented architecture to a content-centric one. Another technique to address this capacity crunch is to improve spectral utilization through new networking paradigms at the wireless network edge. To this end, Device-to-Device (D2D) communications has the potential for boosting the capacity and energy efficiency for content-centric networking. To design and implement efficient content-centric D2D networks, rigorous content modeling and in-network caching mechanisms based on such models are crucial. In this work, we develop a multidimensional content model based on popularity, chunking and layering, and devise caching schemes through this model. Our main motivation is to improve the system performance via our caching strategies. The numerical analysis shows the interplay among different system parameters and performance metrics: while our schemes perform slightly poorer in terms of system goodput, they also decrease the system energy expenditure. Overall, this improvement dominates the loss in the goodput, leading to greater energy efficiency compared to the commonly-used caching technique Least Recently Used (LRU).

In cases of catastrophic events such as natural disasters or physical calamities, current network infrastructure can become inoperative. Furthermore, there are transient events leading to excessive demand surges where it is needed to deploy additional network capacity on-demand. In such cases, rapid network deployments become vital to establish communications and enable networked services. Unmanned Aerial Vehicle(UAV) networks are good candidates for this kind of operation. Software-defined networking and content-centric operation are promising technologies to enable agile control, network visibility and efficient content delivery via centralized optimization in these challenged systems. In this work, we consider an edge network which is composed of UAVs and serves in a content-centric mode with in-network caching and device-to-device (D2D) transmissions. We develop a cache placement and selection scheme for energy efficient operation. We also investigate how such a system performs under different operating conditions.

Information-centric networking (ICN) is a Future Internet paradigm which uses named information (data objects) instead of host-based end-to-end communications. In-network caching is a key pillar of ICN. Basically, data objects are cached in ICN routers and retrieved from these network elements upon availability when they are requested. It is a particularly promising networking approach due to the expected benefits of data dissemination efficiency, reduced delay and improved robustness for challenging communication scenarios in IoT domain. From the security perspective, ICN concentrates on securing data objects instead of ensuring the security of end-to-end communication link. However, it inherently involves the security challenge of access control for content. Thus, an efficient access control mechanism is crucial to provide secure information dissemination. In this work, we investigate Attribute Based Encryption (ABE) as an access control apparatus for information centric IoT. Moreover, we elaborate on how such a system performs for different parameter settings such as different numbers of attributes and file sizes.

Software-defined networking (SDN) is a communication paradigm that brings cost efficiency and flexibility through software-defined functions resident on centralized controllers. Although SDN applications are introduced in a limited scope with related technologies still under development, operational SDN networks already face major security threats. Therefore, comprehensive and efficient solutions are crucial. Especially, large-scale security threats such as distributed-denial-of-service (DDoS) attacks are jeopardizing safety and availability of data and services in these systems. A DDoS attack is aimed at making resources unavailable to legitimate users via overloading systems with excessive superfluous traffic from distributed sources. In this paper, we describe and evaluate a joint entropy-based security scheme (JESS) to enhance the SDN security with the aim of a reinforced SDN architecture against DDoS attacks. In particular, our proposed model devises a statistical solution to detect and mitigate these hazards. To the best of our knowledge, JESS is the first model that utilizes joint entropy for DDoS detection and mitigation in the SDN environment. Since it relies on a statistical model, it mitigates not only known attacks but also unfamiliar types in an efficient manner.

Software Defined Networking (SDN) is a promising solution for addressing challenges of future networks. Despite its advantages such as flexibility, simplification and low costs, it has several drawbacks that are largely induced by the centralized control paradigm. Security is one of the most significant challenges related to centralization. In that regard, Distributed Denial of Service (DDoS) attacks pose crucial security questions in software-defined networks. In SDN architecture, switches send all packets to the controller if they do not have any applicable rules in their flow tables. Basically, controller is the key place that can take initiative in decisions. However, this characteristic results in large communication overhead and delay until a DDoS attack is detected and an appropriate action is activated against attack packets. Therefore, in this work we propose a hybrid mechanism, namely SDNScore, where switches are not simply data forwarders. Instead, they can collect statistics and decide if DDoS attack is in action. Then they coordinate with the controller and act on attack packets in cooperation. SDNScore is a statistical and packet-based defense mechanism against DDoS attacks in SDN environment. Since it has a statistical scoring method, it can detect not only known but also unknown attacks entailing packets that are alike in terms of TCP and IP layer properties. In addition, it does not drop all packets in a flow which includes both attack and legal packets, but rather filters out attack packets using packet-based analysis.

Software-defined networking (SDN) has been proposed as a new networking paradigm which separates the control and data forwarding planes. The controllers deployed as centralized network control entities are crucial for meeting the performance and efficiency requirements of these systems. The placement of these network entities, switch assignment and their load-aware operation are challenging research questions. Although various load-balancing schemes are proposed in the literature, this research topic is yet to be explored adequately. In this work, we discuss load-balancing issues in SDN and propose a load-balancing scheme, namely Cooperative Load Balancing Scheme For Hierarchical SDN Controllers (COLBAS), for hierarchical controller configurations. Moreover, we evaluate the performance of our scheme and investigate important performance factors.

The immense development in mobile devices and the proliferation of ubiquitous cloud-based services have led to a surge in the utilization of remote data centers. These dramatic advances in wireless based services induce a huge traffic flow within the network. However, consequent high load on the network devices may lead to faults and thus an adverse decrease in the user experience. On the other hand, balancing the aggregated multi-flow traffic on ports of network switches is a challenging issue. This work presents a load balancing algorithm implemented in OpenDaylight controller for managing the load on the switch ports by utilizing Software-Defined Networking (SDN) architecture. The switch acts a connector which aggregates traffic from wireless access nodes. An experiment design is constructed with hardware-based OpenFlow-enabled switch and connected wireless hosts. According to the load on the ports, the developed scheme dynamically load-balances the incoming traffic towards the backhaul connection. It uses OpenFlow for gathering statistics and flow rule installation on the switch in an adaptive manner.

The proper adjustment of sleep time in idle mode (a.k.a. DRX-Discontinuous Reception in 3GPP specifications) is critical for mobile device (MD) operation in cellular wireless systems. The dynamic radio environment due to transmission impairments and mobility renders this requirement a nontrivial challenge. Moreover, this issue is aggravated in heterogeneous wireless networks where MDs have to change their camping cell more often. Hence, sleep time in idle mode is supposed to be calibrated to perform timely cell reselection without having the received power fall below a suitable level. In this work, we elaborate on MD sleep time adjustment and determine outage bound for imminent received power under certain assumptions. Moreover, we devise a configurable sleep/wake algorithm that aims to choose the best sleep time without dropping below a predefined received power level. Finally, we evaluate our approach with respect to baseline counterparts to examine the performance and investigate the trade-off between received power quality and average power consumption.

Although spectral resources are scarce while being critical for wireless system performance, their utilization in various frequency bands are shown to be very low. Cognitive radio (CR) concept, where licensed bands are allowed to be used by a secondary network, is proposed as a general paradigm to address this limitation. Moreover, the effects of this deficiency in spectral resource management have been aggravated with the exploding content consumption through wireless networks. In emerging 5G wireless systems, Device-to-Device (D2D) communications and heterogeneous architectures composed of different network tiers are posed as two vital apparatus to alleviate the "capacity crunch". However, the interplay/integration of these different techniques and approaches are yet to be comprehensively explored by research efforts. In this work, we consider this issue and develop an analytical Markovian model for content delivery over satellite integrated cognitive radio networks which can utilize D2D operation mode. We focus on throughput and energy efficiency as key metrics for depicting the system operation. We also investigate the effects of various system parameters on the performance such as cache size, mode preference for content retrieval from different content holders and primary user activity.

We focus on throughput-maximizing, max-min fair, and proportionally fair scheduling problems for centralized cognitive radio networks. First, we propose a polynomial-time algorithm for the throughput-maximizing scheduling problem. We then elaborate on certain special cases of this problem and explore their combinatorial properties. Second, we prove that the max-min fair scheduling problem is NP-Hard in the strong sense. We also prove that the problem cannot be approximated within any constant factor better than 2 unless P=NP. Additionally, we propose an approximation algorithm for the max-min fair scheduling problem with approximation ratio depending on the ratio of the maximum possible data rate to the minimum possible data rate of a secondary users. We then focus on the combinatorial properties of certain special cases and investigate their relation with various problems such as the multiple-knapsack, matching, terminal assignment, and Santa Claus problems. We then prove that the proportionally fair scheduling problem is NP-Hard in the strong sense and inapproximable within any additive constant less than log(4/3). Finally, we evaluate the performance of our approximation algorithm for the max-min fair scheduling problem via simulations. This approach sheds light on the complexity and combinatorial properties of these scheduling problems, which have high practical importance in centralized cognitive radio networks.

MapReduce has emerged as one of the key workloads in today's data centers, which constantly strive for an optimal tradeoff between energy consumption and performance. MapReduce alternates between computation and communication intensive phases with bursty workloads. The challenge to make execution of MapReduce green, lies in controlling server and network resources simultaneously. The related work offers various good solutions for homogenous systems, with the central theme of packing tasks into as small number of servers as possible and thus overlooking the possibility to "sleep" servers and network components. This paper considers a very bursty MapReduce workload with distinct CPU, memory and network requirements executed on heterogenous data centers, where servers have various CPU/memory capacities and execute request in a process-sharing manner. To reduce energy consumption while maintaining a low task response time, we propose an online energy minimization path algorithm, termed GEMS, to schedule MapReduce tasks, in cooperation with sleeping policies on servers as well as the switches. Using Google MapReduce traces, our simulation experiments show that our proposed solution gains a significant energy saving of 35% and meanwhile improves task response times by 35% on heterogenous data centers, compared to policies which are network agnostic or adopt no sleeping schedule. Overall, we achieve greener and faster MapReduce with (surprisingly) only a slightly higher number of servers, by considering energy consumption rather than conventional approach of considering power values only.

Cognitive radio networks (CRNs) are envisaged to alleviate the spectrum and capacity shortage aggravated by the static spectrum allocation. They are crucial for meeting the requirements of wireless traffic explosion emerging with new wireless applications and services. However, the security of CRNs is critical for their practical usage and widespread proliferation. Therefore, the fundamental mechanism of spectrum sensing in these systems has to be investigated from the security perspective. In this work, we define and analyze coordinated attack models for Cooperative Spectrum Sensing (CSS) in CRNs. We devise a simple yet effective countermeasure scheme based on trust management for cooperative sensing. We also provide experimental results to illustrate the performance of these systems under coordinated attacks.

We formulate a scheduling problem that takes into account different hardware delays experienced by the secondary users (SUs) in a centralized cognitive radio network (CRN) while switching to different frequency bands. We propose a polynomial-time suboptimal algorithm to address our formulated scheduling problem. We evaluate the impact of varying switching delay, number of frequencies, and number of SUs. Our simulation results indicate that our proposed algorithm is robust to changes in the hardware spectrum switching delay and its performance is very close to its upper bound. We also compare our proposed method with the corresponding constant switching delay-based algorithm and demonstrate that our suggestion of taking into account the different hardware delays while switching to different frequency bands is essential for scheduling in CRNs.

The growing economical and environmental cost of data centers due to the high energy consumption is becoming a major issue. “Green Data Centers” refers to, energy aware, energy efficient and CO2 emission minimizing designs, protocols, devices, infrastructures and algorithms for data centers. Today's data centers are provisioned for peak load. However, it is shown that servers are idle most of the time. Idle servers and the connected network elements are consuming considerable amount of energy. In this survey, we identify the key enablers of green data center research. Firstly we overview the green metrics that are applicable to data centers. Then we describe the most recent stage of research and give a taxonomy of the related work. We focus on computing and networking proposals for green data centers, even though we briefly describe some other green research related to data centers such as cloud computing, cooling.

Abstract Cognitive radio heralds the next step in the evolution of wireless communications. In this paper, an analytical model for infrastructure based cognitive radio systems is proposed, and its performance is evaluated under bursty traffic scenarios in a multiple cell environment. Performance metrics like probabilities of dropping and blocking for primary and secondary users as well as forced termination and forced frequency handoff for secondary users are investigated, and the analytical model is verified with simulations. In addition to the analytical model, a new resource planning method is proposed to compensate for uneven traffic load distribution. The proposed method considers offered traffic, hop count to the heavily loaded cell, and velocity of mobile users during resource planning and performs better in terms of probability of blocking, dropping, and forced termination. The proposed method is promising in balancing the system performance measures, yet there is room for further improvement for finding a closed formula for the proposed analytical model. Copyright © 2010 John Wiley & Sons, Ltd.

With the increasing need for converged and ubiquitous broadband service support, next-generation mobile radio technologies are posed to be more efficient in different aspects such as energy and spectrum. There are also emerging critical environmental and cost concerns due to the steadily increasing energy consumption and related negative consequences such as greenhouse gas emissions and energy costs. In that respect, energy-wise optimization of satellite communications is crucial considering the objectives of cost improvement and energy efficiency (e.g., due to mobile and small form-factor end-user devices) or the strict energy constraints such as satellite power capacity for resource allocation. However, there are intrinsic challenges such as hardware complexity, algorithmic problems, and design tradeoffs. In this work, various aspects of energy efficiency and satellite networking, ranging from protocols for airborne satellite systems to mobile end-user terminals are reviewed and discussed. In addition, we present emerging factors including dynamic spectrum access, cross-layer design, the integration of space/terrestrial networks, interplanetary Internet, and emergency communications. Moreover, the enabling effect of satellite communications for greener infrastructural systems from the perspective of smart grids, so-called “enabled efficiency,” is outlined beside this “self-efficiency” issue.

We consider the problem of distributed channel selection in cognitive radio (CR) ad hoc networks (CRAHNs) in which CRs have the capability of estimating the primary channel traffic activities. We propose a distributed channel selection scheme referred to as best-fit channel selection (BFC). In BFC each CR selects a channel among the primary user (PU) channels for transmission that best fits to its transmission requirement as opposed to the widely known longest idle time channel selection (LITC) scheme, in which a CR selects the channel that has the longest expected idle time independent of its transmission needs. In a multi-user network LITC may degrade the network performance compared to the BFC. In contrast to the BFC, referred to as non-selfish, LITC is considered selfish since each CR aims to maximize its own benefit and wastes resources that may be utilized by other CRs in the network. Through a set of simulations, we highlight the performance improvement by the BFC scheme over the conventional LITC scheme. Simulation results show that the performance of BFC is significantly superior to that of the LTIC in terms of CRAHN throughput and probability of successful transmission of CRs.

In this paper, we propose an interference aware throughput maximizing scheduler for cognitive radio networks (CRNs) as part of a MAC layer resource allocation framework. In the considered CRN scenario, the cognitive users with multiple antennas are coordinated by a centralized cognitive base station. We evaluate the performance of our proposed scheme using analysis of variation (ANOVA) technique. We also show experimental results for the total throughput for varying number of cognitive users and frequencies.

Cooperative spectrum sensing for dynamic spectrum access to unused licensed spectrum has been proposed as a solution to the spectrum scarcity problem. In this paper, a novel sensing algorithm, Cooperative Sensing with Decision Vector (CSDV), that employs uniform quantizer and a weight vector for global decision logic, is proposed. CSDV method is based on energy detection and performs better than conventional hard decision algorithms such as MAJORITY and M/N in terms of probability of detection and false alarm at the cost of a marginal increase in overhead bits. Probability of detection is maximized for a given probability of false alarm by proposed method via convex optimization. For detailed analysis, CSDV is compared with equal gain combiner scheme, which performs far better than hard decision algorithms, via highest bandwidth requirement. Moreover, robustness of CSDV method to sensing error is analyzed when some nodes always report false decisions to the fusion center.

The performance of impulse radio is investigated for ultra-wideband (UWB) channels and orthogonal M-ary pulse position modulation (PPM) in terms of the maximum achievable information rate, where the outputs of the M-ary correlation receiver implemented through the rake structure with conventional maximal ratio combining are subject to either soft or hard decisions. The major difference observed between the soft- and hard-output systems is that at low values of the mutual information the minimum information bit energy to noise ratio required for reliable communication increases with the constellation size for the hard-output systems. Furthermore, it is demonstrated that independent of the type of the output, achievable rates are considerably low at medium-to-large signal-to-noise ratio (SNR) values in UWB channels compared to those in additive white Gaussian noise channels, as the frequency-selectivity of the UWB channel destroys the orthogonality of the transmitted PPM signals. Interference from other users and constellation size put additional constraints on the achievable rates at high SNR.

Using Virtual Node (VN) approach, network layer handover can be eliminated in earth-fixed LEO satellite systems. However, handover in lower layers could result in significant data loss. In this work we propose a link-layer handover algorithm for VN-based satellite systems: Virtual Node Handover Algorithm (VN-HO). Further, we propose to increment number of satellites per orbit in order to enable soft handover. On the modified system, which can be represented by multi-state virtual network (MSVN) topology, we propose a soft handover algorithm (MSVN-SHO). Relying on test results, MSVN-SHO is faster and smoother than VN-HO, despite a marginal increase in the cost.

The performance of impulse radio is investigated for frequency-selective ultra-wideband (UWB) channels and orthogonal M-ary pulse position modulation (PPM) in terms of the maximum achievable data rate, where the outputs of the M-ary correlation receiver implemented through the rake structure with conventional maximal ratio combining undergo either hard or soft decisions. The major difference observed between the soft and hard decision output systems is that at low code rates increasing the constellation size, M, requires an increase in the minimum signal-to-noise ratio (SNR) per communicated bit for the system with hard decisions. It is demonstrated that independent of the type of decision making, achievable rates in UWB channels are low compared to those in additive white Gaussian noise channels, as the frequency-selectivity of the UWB channel destroys the orthogonality of the transmitted PPM signals. The interference from the other users and the constellation size put additional constraints on the achievable data rates at high values of SNR.

Virtual node (VN) approach is widely used in satellite networks research but it has some deficiencies. In this work, we enhanced VN technique and propose a generic virtual topology model, namely multi-state virtual network (MSVN) architecture. We investigate a new mathematical model for MSVN and present its potential contribution to the overall system availability.

Handover management in Low Earth Orbit (LEO) satellite networks is a challenging task for supporting global mobile communication. A major problem with LEO satellites is their higher speed relative to terrestrial mobile terminals, which move at lower speeds but at more random directions. In this paper we propose a new LEO handover management algorithm, which utilizes the inter-satellite links and buffering capability of LEO satellites aiming at decreasing latency, data loss, and handover blocking probability. This is achieved by the newly introduced Billboard Manager which is used for location updates of mobile users and satellites. The Billboard Manager makes the proposed handover model much more flexible and easier than the current solutions, since it is a central server and supports the management of the whole system. To show the performance of the proposed algorithm, we run an extensive set of simulations both for the proposed algorithm and well known handover management methods as a baseline model. The simulation results show that the proposed algorithm is very promising for seamless handover in LEO satellites.

In this paper, we propose a new N-tier sAtellite Multicast sEcurity Protocol based on multi-recipient Signcryption schemes (NAMEPS). Our protocol is especially designed for very large and highly dynamic satellite multicast systems which require high security and reliability. Our N-tier architecture significantly reduces workload of the satellite layers especially for bandwidth consumption, computation resources and storage requirements. N-tier approach localizes effects of the rekeying operation (forward-backward security) and provides significant performance gain. Moreover, batch keying and ticketing mechanisms are used which additionally reduce workload of the satellite and terrestrial layers. Also, as a novel approach for cryptographic method, our protocol uses multi-recipient signcryption scheme, which provides confidentiality, authentication, unforgeability and non-repudiation together, more efficiently than classical sign-then-encrypt approaches. As a result, NAMEPS has many advantages for very large, dynamic and security critic satellite multicast systems.

Wireless overlay networks (WONs) are multi-layer networks in which mobile nodes (MNs) move freely within cells of the same overlay or between cells of different overlays. Such a structure provides global access to MNs regardless of time and location but poses many challenges. This paper covers the problem of building an efficient handover decision manager (HDM) on each MN so that the MN can decide horizontal and vertical handovers encountered in WONs. The paper studies the current handover decision schemes and proposes a hybrid scheme. The proposed HDM algorithm considers many factors such as the candidate networks' cost, coverage, data rate and traffic load. The algorithm gives accurate and timely decisions and considerably decreases MNs' power consumption at the expense of slightly increased complexity. The simulations, which compare the proposed HDM scheme with two-level thresholding and utility-based schemes, show that the number of unnecessary handovers and MNs' power consumption are decreased considerably while MNs' throughput is not significantly affected by the proposed HDM algorithm.

The approach presented in this paper aims at establishing a bandwidth allocation scheme for use in Geostationary Earth Orbit (GEO) satellite networks. As various multimedia applications necessitate large amounts of capacity, an efficient bandwidth management algorithm comes into prominence in order to provide high quality of service (QoS) to users. The first stage of the algorithm involves determining the portion of bandwidth that should be offered to a Satellite Gateway (SG), while the second stage consists of sharing this allocated bandwidth among different traffic flow types. At this point, the strategic pricing concept which means building a balance between the customer's desires and the network operator's profits emerges. The proposed approach has the objective to solve simultaneously these two consecutive allocation problems and moreover to propose their pricing scheme. Analytical and simulation results demonstrate the effectiveness of the suggested approach in terms of efficient bandwidth usage.

Low Earth Orbit (LEO) satellite constellations have important advantages over Geosynchronous Earth Orbit (GEO) systems such as low propagation delay, low power requirements and more efficient spectrum allocation due to frequency reuse between satellites and spotbeams. However, one of the major problems with LEO satellites is their high speed relative to the terrestrial mobile terminals, which move at lower speeds but at more random directions. Therefore, mobility management becomes more challenging with LEO satellites. Efficient and accurate methods are needed for satellite handovers between the moving footprints produced by the satellite multi-beam antennas. The main concern is providing a reliable service to the user that prevents a communication from being dropped due to a handover. In this paper, we first define the pattern of a satellite by using the fact that a satellite passes over the same geographical area of the Earth in repeating periods of time, and then we propose an efficient handover management strategy for LEO satellites that takes mobility pattern of both satellites and mobile terminals into account. To show the performance of the proposed algorithm, we run an extensive set of simulations both for the proposed algorithm and well known handover management methods as a baseline model. The simulation results show that the proposed algorithm is very promising for seamless handover in LEO satellites.

This paper focuses on the channel capacity of direct sequence code division multiple access (DS-CDMA) and time-hopping pulse position modulation (TH-PPM) for ultra-wide band (UWB) communication systems over multiple-access and additive white Gaussian noise (AWGN) channel. Based on Gaussian approximation for the multiple access interference, an expression of the signal-to-noise ratio is derived for the UWB system using 2nd derivative Gaussian pulse. The information theoretic capacity of the UWB system is expressed as a function of system parameters. Analytical and simulation results show that the capacity of DS-CDMA outperform the capacity of TH-PPM UWB system for high demand environment

In this paper, we propose a new error concealment method for covering up the high packet losses of an original image after its transmission through an error-prone channel. Error-concealment techniques provide a simple framework to compensate these distortions without incurring additional delays and wasting bandwidth resources which are crucial for real-time applications over networks with limited resources. Unfortunately, most of the existing error-concealment techniques work only if the packet losses are smaller than a threshold and/or they are uniformly distributed. Utilizing data hiding techniques is a potential approach to overcome this restriction. We investigated an error concealment technique utilizing discrete wavelet transform (DWT) for embedding macroblock-based BNM (best-neighborhood-matching) information into the original image in order to utilize spatial redundancy. We propose that this technique can be implemented for error-prone channels to combat such degradations in a backward-compatible scheme. We show that the proposed error concealment technique is a promising one, especially for the erroneous channels causing a wider range of packet losses, at the expense of some degradation in the perceptual quality of the original image

In this paper, as part of the adaptive resource allocation and management (ARAM) system (Alagoz, 2001), we propose an adaptive admission control strategy, which is aimed at combating link congestion and compromised channel conditions inherent in multimedia satellite networks. We present the performance comparisons of a traditional (fixed) admission control strategy versus the new adaptive admission control strategy for a direct broadcast satellite (DBS) network with return channel system (DBS-RCS). Performance comparisons are done using the ARAM simulator. The traffic mix in the simulator includes both available bit rate (ABR) traffic and variable bit rate (VBR) traffic. The dynamic channel conditions in the simulator reflect time variant error rates due to external effects such as rain. In order to maximize the resource utilization, both for fixed and adaptive approaches, assignment of the VBR services are determined based on the estimated statistical multiplexing and other system attributes, namely, video source, data transmission, and channel coding rates. In this paper, we focus on the admission control algorithms and assess their impact on quality-of-service (QoS) and forward link utilization of DBS-RCS. We show that the proposed adaptive admission control strategy is profoundly superior to the traditional admission control strategy with only a marginal decrease in QoS. Since the ARAM system has several parameters and strategies that play key roles in terms of the performance measures, their sensitivity analysis are also studied to verify the above foundations.