Information freshness is one of the critical aspects of communication networks. Average age of information (AoI) and peak AoI (PAoI) are the main metrics for evaluating information freshness. Modeling the communication system with a stochastic hybrid system (SHS) is an effective approach for finding these metrics, especially in complex network scenarios. A regular SHS is comprised of a Markov chain (MC) and some stochastic processes evolving according to the state of the MC. The Markovian property of the chain in regular SHSs limits the capability of this approach in analyzing general network scenarios, e.g., when the transmission times of packets follow a general non-exponential distribution. In this work, we focus on the semi-Markovian-SHSs (SM-SHSs). In SM-SHSs, compared to regular SHSs, the Markovian property of the system chain is extended to semi-Markovian property, i.e., the sojourn time in each state follows an arbitrary distribution depending on the next transition in the system chain. We derive theorems for finding the average AoI and PAoI when the communication system is modeled with an SM-SHS. We also propose an age-ordering-aware multi-stream M/G/1/1 queueing system with the assumption of deterministic vacation times for the server and analyze this system using the SM-SHS approach.

In this paper, we study the information freshness in a network with two information classes, where class 1 packets have a priority higher than class 2 packets. We propose a new queueing policy with delayed preemptions, that is, when a class 1 packet arrives while a class 2 packet is in service, instead of the usual immediate preemption, a deadline is assigned for the service of class 2 packets. By the end of the mentioned deadline, if the low-priority packet is still in service, it is preempted. The main goal of this delayed preemption policy is to balance the freshness metrics of the information classes, which is an intrinsic attribute in some applications, e.g., caching of dynamic contents, where the freshness of some contents is more critical than the others. For exponentially distributed deadlines, by exploiting a stochastic hybrid system (SHS), we evaluate the average age of information (AoI) and average peak AoI (PAoI). We also find general formulas for the average PAoIs of the classes for arbitrarily distributed deadlines and use them to find the average PAoI for deterministic deadlines. By numerical results, we investigate the performance of this policy in balancing the average AoIs/PAoIs of information classes.

In this paper, we study the age of information (AoI) in a network consisting of multiple information streams with different priorities sharing a common server. In this network, the transmission of a packet is interrupted whenever a higher priority packet arrives. Regarding the behavior of AoI, for each stream, we consider a single buffer to enqueue the incoming packets based on a quasi-blocking (QB) policy. With the assumption of Poisson packet arrivals, we formulate the AoI and PAoI moment generating functions for each stream, while no assumption is considered for the service times of the packets. We also introduce a new semantic queueing policy. In this respect, we define the semantic (i.e., significance) of a packet as a linear combination of its age and remaining transmission time. When this metric is lower for a packet, the packet is more significant. In this policy, the decision to replace the available packet of a stream with a new arriving one is made based on the significance of these packets. This decision minimizes the sum of the next local peak and end-to-end delay in the AoI function. We investigate the superiority of this policy to the traditional ones in our numerical results.

In this work, we study the age of information (AoI) in a multi-hop multi-path network with$r$distinct independent paths from the source to the destination. Each path is considered as a tandem network consisting of$k$preemptive servers. We consider two different policies for choosing a path to transmit a packet. In the first policy, each packet is randomly assigned to only one path. In the second one, each packet is assigned to all of the paths. In both policies, packets may be delivered out-of-order, which makes the AoI analysis challenging. To overcome this challenge, we exploit the age of link (AoL) concept which enables us to study AoI in multi-path systems. Then, we use a stochastic hybrid system (SHS) approach for finding the average AoI. In the symmetric case where the service rates of the servers are equal, we find a lower-bound on the average AoI, which shows increasing the number of paths is not effective when the number of hops is relatively large.

Sharding in blockchains divides nodes into smaller groups which allow for partial transaction processing, relaying and storage. Accordingly, multiple blockchains (shards) will run in parallel, resulting in an increase in total throughput. Nonetheless, with shards comprised of less nodes, they will be more prone to security issues. In this paper, we propose a denial-of-service (DoS) attack where attackers are nodes that are eligible to participate in the process of intra-shard consensus. They then overflow a specific shard by proposing biased blocks containing cross-shard transactions where their receipts are all aimed at that shard. In particular, we utilize a queueing-theoretic model to evaluate different conditions in which the proposed DoS attack can successfully be performed or on the other hand avoided. We show that this attack can be performed irrespective of means to prevent shard takeover attack, e.g., randomization. Accordingly, for different loads in the system and attackers capabilities, we derive the maximum number of shards under which this attack can be averted, so that the system can perform safely.

Network slicing, a key component of 5G, enables simultaneously running incompatible service types on a common infrastructure. Inter-slice isolation, as a key requirement of slicing, ensures that slice activity, i.e., containing a flow under transmission, does not affect the activity of other slices. Isolation in radio access network (RAN) slices is challenging due to interaction between slices. In fact, due to direct or indirect overlap among frequency channels in RAN slices, interference in inevitable, leading to interaction. In this paper, we propose an analytical model to analyze interference-coupled multi-cell RAN slicing where the interaction among slices results in dynamic behavior of slices. To this end, we map our scenario onto a suitable state-dependent queueing network, propose an iterative algorithm to obtain approximately the network steady-state probability distribution, and derive conventional QoS metrics (average delay and throughput). To quantify isolation, we define some new key performance indicators (KPIs) that show how changes in interfering slices affect the QoS metrics. Finally, we propose an interference-aware slice channel allocation policy that significantly reduces overlapping frequency channels. Numerical results demonstrate the accuracy of our analysis and the efficacy of the proposed policy in improving isolation-based KPIs compared to some other allocation policies.

In this paper, we propose a cache update policy for wireless networks considering dynamic popularity for file requests. Our network scenario is a wireless network comprised of some cache-equipped access points (APs) which are deployed densely in an area and have connections with core network servers. We model the dynamics of file requests as Markov-modulated Poisson processes. Considering the congestion-dependent delay of APs' services and their overlapping coverage areas, we model the cache service for the cache-missed requests, as a stochastic game in which a Vickrey–Clarke–Groves (VCG) mechanism is exploited at each stage of the game as our proposed file routing policy, and the APs decide independently how to update their caches regarding the routed files. To this end, the APs' utilities are defined based on long-term average file delivery delay including the queueing delay in APs. By finding the Nash equilibrium of the game, we propose policies for both delivery and cache update of dynamic contents. Finally, by comparing numerical results of our proposed scheme with some conventional caching schemes, we show significant improvements in network performance in terms of file delivery delay in different conditions.

In this paper, we analyze the effect of implementing variable backoff algorithms on the average peak age of information (PAoI) and the average age of information (AoI) in slotted ALOHA networks. To this end, we first analytically derive the average PAoI in exponential backoff slotted ALOHA when the number of backoff stages is finite. We also show that the reduction in average PAoI achieved by the exponential backoff algorithm can significantly increase the average AoI, which is not desirable. Then, we propose an age-based backoff algorithm and present the intuition behind it. In contrast to exponential backoff, our proposed age-based backoff algorithm reduces the average PAoI significantly, while changing the average AoI limitedly. The numerical results confirm our analytical results as well as the superiority of the proposed age-based backoff algorithm over exponential backoff.

Sharding has shown great potential to scale out blockchains. It divides nodes into smaller groups which allow for partial transaction processing, relaying and storage. Hence, instead of running one blockchain, we will run multiple blockchains in parallel, and call each one a shard. Sharding can be applied to address shortcomings due to compulsory duplication of three resources in blockchains, i.e., computation, communication and storage. The most pressing issue in blockchains today is throughput. In this paper, we propose new queueing-theoretic models to derive the maximum throughput of sharded blockchains. We consider two cases, a fully sharded blockchain and a computation sharding. We model each with a queueing network that exploits signals to account for block production as well as multi-destination cross-shard transactions. We make sure quasi-reversibility for every queue in our models is satisfied so that they fall into the category of product-form queueing networks. We then obtain a closed-form solution for the maximum stable throughput of these systems with respect to block size, block rate, number of destinations in transactions and the number of shards. Comparing the results obtained from the two introduced sharding systems, we conclude that the extent of sharding in different domains plays a significant role in scalability.

In this paper, we concentrate on the peak age of information (PAoI) in a discrete-time slotted ALOHA network comprised of$\boldsymbol {M}$buffer-less nodes, capable of keeping just one packet at each slot. In this network, a collision happens whenever at least two nodes transmit their packets simultaneously. Thus, there is some interaction among queues, and the transmission delay of a packet might prolong more than one slot. The packets are generated at each node stochastically and independently. The nodes follow the preemptive queueing policy. In this network, we propose a trellis-based model to analyze packet system time and derive the exact average PAoI of symmetric and asymmetric slotted ALOHA networks. We confirm our analysis by simulation results in different conditions. By exploiting numerical results, we optimize the average PAoI of the symmetric slotted ALOHA network, find the PAoI-constrained regions, and compare the PAoI of slotted ALOHA networks with and without retransmission of the failed packets.

In this paper, we analyze the saturation throughput of a cognitive WLAN overlaid on a primary OFDMA TDD network (e.g., LTE or WiMAX). In this scenario, after the contention among the secondary nodes, the winner node transmits its data packet in the empty resource blocks (RBs) of downlink and uplink subframes of the primary network. Regarding the OFDMA structure as well as time-scheduled resources in the primary network, the time duration of opportunities for the secondary network does not follow simple exponential on-off pattern. To model the dynamic behavior of opportunities for secondary nodes as well as contentions to exploit the opportunities, we propose an analytical model comprised of a discrete-time Markov chain and two inter-related open multi-class queueing networks (QNs). The effects of the random number of empty resource blocks at different frames as the result of random amount of download and upload data, random packet transmission time at WLAN, the dependency of the number of empty RBs at consecutive frames, and the details of 802.11 MAC protocol are included in our analytical approach. We include different resource allocations in the primary network in our analysis. Simulation results confirm the accuracy of our analytical approach in different conditions.

Frame aggregation (FA) mechanisms improve the throughput of WLANs. In this paper, the effect of the FA mechanism on the throughput of wireless local area networks (WLANs) has been investigated. To this end, we propose an analytical model in order to analyze an IEEE 802.11n network comprised of an access point (AP) and several conventional nodes (CNs), all in the coverage area of each other. With respect to the heavier download traffic compared to the upload one, in our scenario, only the AP uses an FA mechanism and the other nodes use the basic IEEE 802.11 standard. In our proposed analytical model, the maximum downlink (DL) throughput is derived. Regarding the asymmetry among nodes, our analytical model consists of two different queueing networks: one for the AP and the other one for CNs. We verify the accuracy of our analytical results by simulations, i.e., less than 5% mismatch between the analytical and simulation results. We show that there is a tradeoff between the DL saturation throughput and performance of CNs. In other words, the FA improves the AP saturation throughput at the cost of a little degradation of the performance for CNs.

In this paper, we propose a new packet prioritization scheme in order to exploit the full-duplex (FD) capability of the access point (AP) more efficiently, in an asymmetric IEEE 802.11-based WLAN, i.e., only the AP has the in-band FD communications capability. In this respect, we consider a modified version of IEEE 802.11 MAC protocol such that at any transmission opportunity in which AP has the role of the transmitter or the receiver, it does the best to select a partner packet to be simultaneously received or transmitted, respectively. The key feature of our proposed partner packet selection scheme is to reduce the idle time intervals that in an FD transmission opportunity, due to different transmission times of the packet and its partner usually exist. To this end, we consider the packet lengths, the waiting time of the packets as well as the interfering effects of the two simultaneously active links on each other as the effective factors in prioritizing the packets to be selected as the partner. We map the problem onto finding a two-sided stable many-to-many matching table. Our numerical results indicate the high efficiency of the proposed scheme in exploiting the time, i.e., decreasing idle time intervals as well as increasing the throughput at the cost of controlled relaxation of the average delay.

In this paper, we propose a data offloading algorithm in a network comprised of a macro base station and a few number of WiFi access points with overlapped coverage areas. The main goal of our algorithm is how to assign offloaded mobile stations (MSs) to access points (APs). Our approach in proposing the algorithm is based on mapping the problem onto finding a suitable matching algorithm, in order to minimize the average delay of the offloaded packets as one of the main QoS parameters on the one hand and to maximize the utility of the APs on the other hand. The utility of each AP is considered to be a combination of monetary benefit due to offloading service and the cost due to extra energy consumption. Since the preferences over APs from the viewpoint of MSs are dependent on each other, our problem is in fact a matching problem with externalities. Thus, in order to obtain a suitable matching, we apply swap matching algorithm to reach a final matching satisfying two-sided exchange stability. Our numerical results show the superiority of our proposed algorithm when compared to two simple assigning algorithms based on maximum SNR and traffic load balancing.

In this paper, we derive optimal policies for cooperation of a wireless node in relaying the packets of a source node, in a random access environment. In our scenario, the source node sends its packets by its harvested energy and the relay node exploits its harvested energy in relaying the source packets not detected successfully at the destination. The relaying policies determine whether the relay node accepts or rejects the unsuccessfully transmitted source packets and how the relay node prioritizes the accepted source packets to its own packets. The optimization goal is to minimize the average transmission delay of source packets with and without a constraint on the average transmission delay of relay packets. We derive the optimal policies in static and dynamic formulations. In static one, optimum rejection and prioritization probabilities corresponding to the aforementioned aspects of relaying policies are derived. To this end, we model the status of the relay node by a quasi-birth-death process, derive the required parameters, and apply some numerical optimization methods. In dynamic formulation, the relay node optimally decides based on its status by employing a constrained Markov decision process. By numerical results, we show the efficiency of the optimal relaying policies in different conditions.

Spectrum mobility in cognitive radio networks not only enables the secondary users to guarantee the desired QoS of the primary users but also grants an efficient exploitation of the available spectrum holes in the network. In this paper, we propose a probabilistic approach in determining the initial and target channels for the handoff procedure in a single secondary user network. To characterize the network, a queuing theoretical framework is introduced, and “stay” and “change” handoff policies are both addressed. The performance of the secondary user in terms of average sojourn and extended service times for secondary connections is analyzed, and convex optimization problems with the objective of minimizing those times as well as analytical solutions are presented. Simulation results confirm the validity of our analytical approach.

In this paper, we propose distributed static and dynamic optimal policies in a random access environment, comprised of energy harvesting (EH) nodes, in order to maximize the sum throughput. In static approach, each EH node exploits an optimal constant power to transmit its packets. However in dynamic one, the EH nodes adjust their transmission powers based on their network information, leading to exploit variable transmission powers. In static algorithm, the maximization is done through modeling energy buffer of EH nodes by a two-dimensional discrete time Markov chain which includes the effect of on-line charging and limited energy buffer. However, in dynamic approach, the variable power is allotted to EH nodes through modeling the problem as a Markov decision process. We observe that dynamic approach outperforms the static one by suitable management of collisions and available energy. Simulation results confirm our analytical approach.

In wireless body area networks (WBANs) it is necessary to devise an energy-efficient MAC scheduling mechanism which is capable of meeting strict QoS requirements. In this paper, special characteristics of WBAN channels, namely, the slow fading, the periodicity of fading, and the correlation among the channels have been exploited to formulate the sensor scheduling problem as a partially observable Markov decision problem (POMDP). Specific algorithms based on value iteration and pruning have been proposed in order to reduce the computational burden associated with the corresponding POMDP. The proposed scheduling mechanism is compared against a TDMA scheduling for a three-sensor network, and an average 22-32% improvement in energy consumption and slight improvement in reliability is reported.

The authors investigate the content distribution among the vehicles of a cluster in a vehicular ad‐hoc network, exploiting network coding. The vehicles collaborate to disseminate the coded data packets, received from a roadside info‐station based on IEEE 802.11 medium access control (MAC) protocol. Two types of network coding are considered: random linear network coding (RLNC) over a large finite field and random XORed network coding (RXNC). An analytical model is proposed to address the effect of random access MAC as well as the correlation among received coded packets on the performance of content distribution. First, a p ‐persistent carrier sense multiple access approximation for IEEE 802.11 MAC is adopted, to derive the expected amount of time necessary to deliver the whole information (a data file) to the vehicles, that is, content distribution delay, based on RLNC. Second, the content distribution delay for RXNC is investigated. In this respect, the authors determine the probability of a newly received packet to be innovative for RXNC and characterise the probability that all nodes succeed to retrieve the data file, that is, content delivery ratio. Finally, the success of content distribution process for erasure channels is assessed.

This paper presents an analytical study of the stable throughput for multiple broadcast sessions in a multi-hop wireless tandem network with random access. Intermediate nodes leverage on the broadcast nature of wireless medium access to perform inter-session network coding among different flows. This problem is challenging due to the interaction among nodes, and has been addressed so far only in the saturated mode where all nodes always have packet to send, which results in infinite packet delay. In this paper, we provide a novel model based on multi-class queueing networks to investigate the problem in unsaturated mode. We devise a theoretical framework for computing maximum stable throughput of network coding for a slotted ALOHA-based random access system. Using our formulation, we compare the performance of network coding and traditional routing. Our results show that network coding leads to high throughput gain over traditional routing. We also define a new metric, network unbalance ratio (NUR), that indicates the unbalance status of the utilization factors at different nodes. We show that although the throughput gain of the network coding compared to the traditional routing decreases when the number of nodes tends to infinity, NUR of the former outperforms the latter. We carry out simulations to confirm our theoretical analysis.

This paper presents an analytical study of average delay and throughput in a two-way relay network exploiting network coding to exchange source packets, where arrival and departure of packets are stochastic. In this case, a fundamental problem for the relay node is whether to wait in order to obtain a coding opportunity, leading to reduction of the number of transmissions, or sending a packet (coded/uncoded) whenever it has a transmission opportunity, leading to reduction of the packet delay. In order to address the fundamental trade-off between packet delay and transmission power, we develop three network coding schemes based on power-delay constraint of the application. We devise a theoretical framework to compute the average delay and stability region for each proposed scheme and compare the performance of network coding and traditional routing. Our results reveal that network coding may deliver packets with either larger or lower delay compared to traditional routing, depending on the selected scheme. Unlike the previous works in this area, in order to include channel loss due to noise, interference, etc., we consider probabilistic transmission for all packets. The transmission probabilities depend on the nature (coded/uncoded) and destination of packets, which are generally different for coded and uncoded packets. We carry out simulations to confirm our theoretical analysis.

In this paper, we evaluate the effect of energy constraints on the performance of a simple network comprised of wireless nodes with energy harvesting capability. In this scenario, wireless nodes contend with each other based on slotted Aloha protocol in order to transmit a packet. Packet transmission occurs provided that enough energy exists in the energy buffer. We propose an analytical model based on a closed queueing network (QN) to include details of data and energy buffers as well as random access MAC protocol. We show how energy limitation affects the MAC design parameters, e.g., contention window size, in order to optimize the performance of the network. Moreover, we evaluate the effect of energy constraints on maximum stable throughput, stability region, and packet drop rate. We also validate our analytical model by simulation.

In this paper, we focus on a cognitive network scenario, comprised of a WLAN overlaid on a network with time-scheduled primary users. WiMAX is an example of such primary networks. For time-scheduled primary users simple On-Off traffic model with exponential durations is not valid anymore. In this scenario, the cognitive nodes (CNs) hear downlink map (DL-MAP) and thus, know the frequency and time locations of all allocated slots at each frame. Then, cognitive nodes contend with each other in order to transmit their fixed size packets based on IEEE 802.11 MAC protocol. Since the number of empty slots at each frame is variable each packet transmission in cognitive network prolongs a random number of frames. By mapping the status of each CN on an open queueing network, including the details of the contention status with the other CNs as well as the statistical distribution of empty slots we are able to derive the saturation throughput of the cognitive WLAN. Finally, we derive the saturation throughput of cognitive network versus the number of CNs as well as the packet arrival rate at WiMAX in downlink direction and confirm our analytical results by simulation.

In this study, the authors propose an analytical model to evaluate the maximum stable throughput and average delay of a cognitive IEEE 802.11-based wireless local area network (WLAN) overlaid on uplink band of a cellular network. The main feature of the proposed model is to include different status of the cognitive users, that is, different spectrum opportunities for different secondary users, as the result of dynamic nature of primary users as well as different locations of the cognitive users relative to primary ones. The proposed model has been founded on an open queueing network comprised of several queueing nodes equivalent to different states of a typical secondary user. By mapping the details of MAC scheme of the cognitive WLAN and dynamic nature of spectrum opportunities onto suitable parameters of the proposed analytical model and writing the corresponding traffic equations, the authors are able to find the maximum stable throughput, that is, the maximum rate of packet generation at the cognitive nodes guaranteeing the stability of all nodes. Below this rate, that is, at the rate when all cognitive nodes are in non-saturation mode, with resort to the proposed analytical model the authors are able to evaluate the average delay comprised of the queueing delay as well as the transmission delay. The authors also show the applicability of our approach in evaluating the effect of different parameters of the cognitive network scenario, for example, the number of users, activity factors etc., onto the maximum stable throughput and non-saturation average delay. Simulation results confirm the validity of the authors analytical approach.

In this paper, we propose an analytical approach to compute the probability of connectivity for one-dimensional ad hoc networks. The proposed analysis gives the exact probability of connectivity for an arbitrary distribution of nodes, provided that nodes are independently and identically distributed. We conduct separate analyses for two cases; in the first case, the number of nodes varies by time under a stationary distribution and in the second case, there is a fixed (known) number of nodes in the network. Using the approaches presented in this work, we are able to derive closed-form formulas for the probability of connectivity for some spatial distributions, while for more complicated distributions, our approach leads to tractable numerical algorithms. As an example, we apply our method to a special case (uniform distribution) and derive a closed-form formula for its probability of connectivity. Finally, we confirm the validity of our analytical approach by simulation for several distributions and show higher accuracy and applicability of the proposed approach compared with existing methods.

In this paper, we consider a broadband secondary transmitter-receiver pair which interferes with N narrowband primary users and study the effect of cognition and cooperation on the maximum stable throughput. In our study we focus on four transmission protocols as well as two channel types, i.e., flat fading and frequency selective fading. In the cooperative protocols, the broadband transmitter relays the packets of the primary users which have not correctly decoded at the primary receiver. The analysis includes random packet arrivals at the transmitters which may impact on the maximum stable throughput. Moreover, sensing errors at the secondary user are considered. In this paper, we derive the exact stability region for non-cooperative protocols and inner bounds for cooperative ones. The results reveal that depending on the channel states, the cooperative protocols may provide significant performance gains over non-cooperative protocols. Numerical results indicate that in the frequency selective channel, independent and simultaneous parallel transmissions in the available subbands are preferred, while in the flat fading channel, a non-parallel transmission in the total available bandwidth is recommended. In part II of our paper, we investigate the impact of cognition and cooperation on the delay performance of the protocols introduced in this paper.

In this paper, we propose an analytical model to evaluate the maximum stable throughput of a cognitive IEEE 802.11-based WLAN sharing the downlink band of a cellular network. Our model has been found on an open queueing network which includes both asymmetric and non-saturated aspects of secondary nodes as well as the time-varying nature of the channel due to intermittent primary nodes. By mapping the details of MAC scheme of the cognitive WLAN, regarding the dynamic nature of spectrum opportunities, onto suitable parameters of the proposed queueing network and writing the corresponding traffic equations, we are able to find the maximum stable throughput, i.e., the maximum rate of packet generation at the cognitive nodes guaranteeing the stability of all nodes. Simulation results show the validity of our analytical approach.

In this paper, we evaluate how traffic-load dependent vehicle routing at intersections is able to improve the connectivity status of all streets. To this end, we consider a VANET scenario, comprised of several streets and intersections. Then, we focus on two vehicle routing algorithms, one based on the distance to destination, i.e., traffic-load independent (TLI) algorithm, and another one based on both distance to destination and traffic load status of the local streets, i.e., traffic-load dependent (TLD) algorithm. By employing a simple mobility model based on an open BCMP queueing network, we derive the spatial traffic distribution at two cases. Afterwards, we propose a simple algorithm in order to find the probability of connectivity at each street. By comparing the TLI and TLD algorithms, we will observe significant improvement on the probability of connectivity for different streets, in the case of TLD.

In this paper, we evaluate the effect of power randomization on the saturation throughput of a WLAN comprised of four classes of users, corresponding to four access categories (ACs) of IEEE 802.11e EDCA. To this end, we consider a specific number of power levels for all users. By some simplifications, we find the probability distributions for the power levels at each class in order to optimize the saturation throughput of a specific class. We evaluate the effect of such optimization onto the saturation throughput of other ACs as well as the saturation throughput of the whole network. Finally, we present some numerical results to show the effect of our optimization in different conditions.

In this study, the authors propose an analytical model to evaluate the maximum stable throughput for unicast services in vehicular ad hoc networks. In this respect, the authors employ two queueing networks (QNs) to model the mobility patterns of the vehicles as well as the multi-hop packet transmission scenario. In the proposed model, the authors map the features of IEEE 802.11, as well as the details of multi-hop packet transmission, regarding the dynamic status of vehicles, onto suitable parameters of the QNs. In the authors' modelling approach, they take the details of MAC and routing schemes into account by classifying the vehicles based on their mobility patterns and considering their dynamic status in average. By writing traffic equations and applying the stability condition, the authors compute the maximum stable throughput of the network, that is, the maximum rate of packets successfully received at the destinations while all vehicles are in stable conditions. In the last part of the study, the authors show the effect of some network parameters onto the maximum stable throughput and confirm the validity of their model by simulation.

In this paper, we evaluate the saturation throughput for an IEEE 802.11 based wireless network considering capture effect at the receiver, while nodes transmit with random powers. In this respect, we consider a scenario consisting of a specific number of wireless nodes. Then, we derive the transmission as well as collision probabilities with respect to the perfect capture effect. In order to maximize the saturation throughput we set up an optimization problem and obtain how to compute optimum values for the probabilities corresponding to different power levels. By providing the numerical results, we deduce that power randomization may lead to a significant improvement in saturation throughput.

In this paper, we propose a new analytical model for stable throughput evaluation of wireless network coding. In this new approach we consider the arrival and departure rates in and from the wireless nodes, respectively, in steady state. Our analytical model is founded on a multi-class open queueing network. In this model, we include two basic processes of network coding, i.e., packets combination and packets multicasting, in a suitable manner considering the constraints of the queueing networks. In this respect, we consider the coded packets as new classes of customers. By solving the related traffic equations and applying the stability condition, we compute the maximum stable throughput, i.e., the maximum packet generation rate at which the packets reach their destinations with finite delays. We apply our approach to a symmetric WLAN with unicast flows and a slotted random access MAC scheme, and compute the maximum stable throughputs for the cases of simple routing and network coding, distinctly. Finally, we confirm our analytical results by simulation.

In this paper, we propose the object pursuing based efficient routing algorithm (OPERA) suitable for vehicular ad hoc networks (VANETs), esp. in sparse situations. The proposed algorithm is applicable for both moving and fixed destinations. It is based on considering static nodes at each intersection. In this algorithm, we optimize the decision making at intersections, with respect to the connectivity and feasibilty of the roads. To this end, we consider the average delay of each road as the connectivity metric, and the vehicle availability in the transmission range of the intersection as the feasibility metric. By exploiting the related metrics, we select the next road to forward the packet in order to minimize the overall delay. We also include a pursuing phase in our algorithm, in order to capture the moving destinations. The simulation results indicate the superiority of our proposed algorithm, compared to previous ones.

In this paper, we propose a new analytical model in order to evaluate the throughput of a wireless tandem network coding. Our analytical model is based on a multi-class open queueing network. In this model, we include two basic processes of network coding, i.e., packets combination and packets multicasting, in a suitable way considering the constraints of the queueing networks. To this end, we consider the coded packets as new classes of customers. In our model we consider the arrival and departure rates in and from the wireless nodes in steady state. By solving the related traffic equations and applying the stability condition, we compute the maximum stable throughput, i.e., the maximum packet generation rate at which the packets reach their destinations with finite delays. We apply our approach on a simple and yet fundamental model of wireless tandem networks with multicast flows and two different MAC schemes, i.e., scheduled access and slotted random access and then compute the maximum stable throughputs for the cases of simple routing and network coding, distinctly. Finally, we confirm our analytical results by simulation.

The authors propose a new analytical model based on BCMP closed queueing networks in order to evaluate the performance of IEEE 802.11 DCF MAC protocol when all nodes are in the transmission range of each other, that is, a single hop wireless ad hoc network. By the proposed model, some performance metrics such as saturation and non-saturation throughput, distributions of channel access delay and the number of packets in the MAC buffer are derived. An extension of the proposed model is used for the analysis of IEEE 802.11e EDCA and the same performance metrics are evaluated for this protocol. Analytical results on IEEE 802.11e prove that differentiation in service is possible and channel share for each service type may be well assigned by tuning the MAC protocol parameters. Simulation results show consistency with our analytical results.

In this paper we introduce a novel cross layer design between MAC and physical layers. Our novel design is based on controlling the adaptive modulation and coding (AMC) transmission mode at the physical layer according to the queue length of finite buffer at the data link layer and each transmission mode of AMC. The aim is optimizing system performance over a wireless link, preserving the important quality of service (QoS) parameter, packet average delay time. Analytical expressions such as packet drop probability, channel packet error rate, packet loss rate and packet average delay time are derived both analytically and through simulations according to the system and channel parameters. Using these expressions, a constrained optimization problem is solved numerically to maximize the overall system throughput, preserving packet average delay time.

In this paper, we compute lower and upper bounds for the throughput capacity of an ad hoc network overlaid on a cellular network. The ad hoc network is comprised of a specific number of wireless cognitive nodes that opportunistically exploit the inactive frequency channels in the cellular network. In this respect, we employ a model recently proposed for single-channel mobile ad-hoc network after some minor modifications. The proposed framework consists of two queueing networks, a closed BCMP queueing network comprised of M/G/co nodes capable of mobility modeling, and an open BCMP queueing network comprised of symmetric M/G/l nodes capable of modeling the packet transmission process. By including the results of the first queueing network and mapping MAC and routing schemes as well as the opportunistic behavior of cognitive nodes onto suitable components of second queueing network we are able to find lower and upper bounds for throughput capacity. We apply our approach in several conditions and confirm our analytical results by simulation.

Cellular CDMA systems have to trade user capacity to increase cell coverage. Moreover, coverage of CDMA is uplink-limited because uplink channels are not orthogonal and transmit powers of mobile stations are limited. In this paper, we propose a coverage-dependent dynamic channel allocation (DCA) method for TDMA-CDMA. In this method, different uplink timeslots have different level of coverage-capacity tradeoff, i.e., Non-homogeneous coverage-capacity tradeoff (NHCCT). This method reduces uplink power consumption and improves coverage-capacity tradeoff, compared to load balancing DCA method. Finally, we verify our approach by numerical analysis and simulation.

In this paper, we propose an analytical framework in order to compute the throughput capacity of a multi-hop ad hoc network with a finite number of mobile wireless nodes. The proposed framework consists of two related queueing networks; a closed BCMP queueing network to represent the mobility model of the wireless nodes and an open BCMP queueing network comprising symmetric M/G/l nodes to represent the multi-hop packet routing process from sources to destinations. In this respect, we consider very simple MAC and routing schemes and then map the related parameters onto several components of the queueing network. By solving the linear traffic equations corresponding to concerned queueing networks and the stability requirement of each node, we obtain throughput capacity, i.e., the maximum throughput with which the packets can be successfully received with finite delay. Finally, we compute the throughput capacity for different number of nodes and several mobility patterns and verify our approach by simulation.

In this paper, we propose a new modeling approach for analytical evaluation of normalized throughput and average backoff time for IEEE 802.11 MAC standard in non-saturation mode and with Poisson arrivals. To this end, we map different stages of distributed coordinated function (DCF) onto different components of a closed multi-class BCMP queueing network with arbitrary service time distribution. At the last part of the paper, we illustrate the applicability of the proposed approach by some numerical results in both saturation and non-saturation modes and obtain average backoff time for different arrival rates.

In this paper, we propose data traffic shaping via leaky bucket in order to reduce outage probability and enhance capacity of voice users for uplink variable spreading gain code-division multiple-access (VSG-CDMA) cellular networks. In order to analyze the effect of leaky bucket mechanism, we employ a closed Jackson queueing network with arbitrary service time distributions to model different states of a typical traffic-shaped data user. By solving the concerned queueing network, we obtain the steady state probability with which a typical data user exist at each state. By aggregating the effects of all data and voice users we obtain mean and variance of interference and compute the outage probability for different number of voice users. At the last part of the paper, we show the efficiency of the proposed traffic shaping on capacity enhancement, at the cost of delay degradation for data users, in different conditions.

In this paper, we focus on the reverse link traffic analysis of a code-division multiple-access (CDMA) cellular network in dynamic environments. In this respect, we propose a new and flexible traffic model, which takes into account the interference-limitedness attribute of CDMA capacity as well as its soft-handoff feature. This new traffic model is developed according to an interference-based call admission control (ICAC) method and a geographical structure with three regions. The main advantage of this traffic model is in its flexibility when we consider different traffic conditions including time-varying status of traffic in the neighboring cells.

In this paper, we propose a general mobility model suitable for wireless multimedia networks. Our model is based on splitting a region into subregions. Furthermore, we make an analogy between subregions as well as their inter-connections with a multi-class Jackson queueing network comprising of infinite-server nodes. The main attribute of such a network is due to its product-form stationary distribution. Using this model, we are able to obtain a closed analytical form for the spatial traffic distribution corresponding to a specific number of network-connected users with different classes of service and mobility in a typical region. Also, we show the flexibility obtained by the proposed mobility model in representing some general distributions such as sum-of-hyper-exponentials (SOHYP), hyper-Erlang and Cox which were previously suggested to model mobility-related statistical parameters, e.g., cell dwell time and channel holding time. Finally, we apply the proposed model to a few mobility scenarios and obtain the resultant active user's location density.

One of the most prominent features of code division multiple-access (CDMA) cellular networks is their ability for applying soft-handoff. This type of handoff results in a better support of seamless communication services, capacity enhancement, QoS improvement, etc. Because of the existence of more parameters and flexibilities compared to hard-handoff, an optimum solution for soft-handoff management and admission control for new and handoff calls is necessary. We propose a new algorithm with two thresholds for admission of new and handoff calls, and with two decision boundaries for controlling of handoff traffic. We compare this algorithm with a simpler one with only one decision boundary, by employing a general and flexible 3-dimensional framework with respect to important traffic parameters including loss probability, carried traffic, blocking and dropping probabilities, and show that our algorithm can result in less loss probability as well as less blocking and dropping probabilities with more control over traffic growth in the cell.