The rapid expansion of the Internet of Things (IoT) has created a growing demand for large-scale sensor deployment. However, the high cost of physical sensors limits the scalability and coverage of sensor networks, making fine-grained sensing difficult. Inductive Spatio-Temporal Kriging (ISK) addresses this challenge by introducing virtual sensors that infer measurements from physical sensors, typically using graph neural networks (GNNs) to model their relationships. Despite its promise, current ISK methods often rely on standard message-passing and generic architectures that fail to effectively capture spatio-temporal features or represent virtual nodes accurately. Additionally, existing graph construction techniques suffer from sparse and noisy connections, further hindering performance. To address these limitations, we propose DarkFarseer, a novel ISK framework with three key innovations. First, the Style-enhanced Temporal-Spatial architecture adopts a temporal-then-spatial processing scheme with a temporal style transfer mechanism to enhance virtual node representations. Second, Regional-semantic Contrastive Learning improves representation learning by aligning virtual nodes with regional component patterns. Third, the Similarity-Based Graph Denoising Strategy mitigates the influence of noisy edges by leveraging temporal similarity and regional structure. Extensive experiments on real-world datasets demonstrate that DarkFarseer significantly outperforms state-of-the-art ISK methods.

Missing values are prevalent in multivariate time series forecasting, especially when certain variables are entirely missing, posing a significant challenge to traditional methods. Two-stage models that combine imputation and forecasting methods are prone to introduce bias and lead to error accumulation. In contrast, existing end-to-end forecasting models with missing data recovery components fail to ensure data consistency when missing variables. Diffusion models, known for their robust generative capabilities, prefer to generate consistent results based on the available observations. Consequently, we propose a novel end-to-end denoising diffusion model named DiffMissing for multivariate time series forecasting with variable missing. DiffMissing employs a contextual conditional encoder to extract local and global contextual information from the observed variables, assisting the denoising network in generating missing variables that align with the true distribution. Meanwhile, the dynamic interaction between observed and missing variables is modeled through a carefully designed adaptive sparse attention, ensuring consistency among variables. Extensive experimental results show that DiffMissing outperforms existing methods in prediction performance on multiple real-world datasets, especially in the high missing rate scenario of 90%, where the MAE is improved by an average of 9.90% over the best baseline.

This paper investigates a hybrid service system with a cloud server and an in-house server. We consider two different scenarios: a hybrid service system with orbit space and a hybrid service system without orbit space. In the hybrid service system with orbit space, customers who fail to enter the cloud server can choose to join the in-house subsystem or to enter an orbit space and retry the cloud server. An admission control mechanism based on queue-length limitation is adopted to adjust whether the cloud service resources are open to customers. When the cloud server cannot be accessed immediately, some customers send their jobs to the in-house subsystem, while others (called opportunists) try to send their jobs to the cloud server again. We obtain the optimal queue-length limitation for a given retrial rate. The service provider and customers are different stakeholders, and their market forces are also different. Therefore, it is more realistic to explore the game relationship between them by using dynamic game theory. We can also explore the joint optimums of the queue-length limitation and the retrial rate in the framework of the Stackelberg game. Finally, by comparing with the hybrid service system without orbit space, we discuss the significance of the existence of orbit space, and gain management insights. It is found that the existence of opportunists may benefit the service provider, although they significantly harm social interests, regardless of whether they are cooperative or non-cooperative; therefore, opportunists are encouraged in some situations. Numerical analysis shows that adding a retrial orbit to a hybrid cloud service system with certain input parameters may even more than triple the service provider’s revenue.

The optimal admission control for secondary users (SUs) using blockchain technology in a cognitive radio (CR) network is investigated in this paper. When an SU comes to the system, it will decide to either enter the system, or give up its service and then leave the system based on the current number of PU and SU users in the network. SUs are linked as a block in the waiting area to access the spectrum in an opportunistic way without interfering the operations of PUs. When a PU arrives, if the band is occupied by SU(s), the SU service on the band is interrupted and SU(s) is then placed back to the waiting queue. Admitting an SU would bring a reward to the system provider but holding an SU in the system would also incur an expense to the provider. We concentrate on the optimization problem of when to admit or reject an arriving SU in order to achieve the maximum total discounted expected reward for any initial state. By establishing a discounted Continuous Time Markov Decision Process (CTMDP) model, we verify that the optimal policies for admitting SUs are state-related control limit policies. An extensive numerical analysis is implemented to show how to determine the value of optimal threshold and of the corresponding maximum objective function. Especially, a simulation by using the idea of the neural network and machine learning is implemented to show how to determine the optimal threshold value for any new input parameters through learning process for a given input parameters. The idea and the corresponding result of this paper can be applied in designing optimal cognitive radio networks.

The Internet of Things (IoT) is the internetworking of a variety of devices, including sensors. Among all sensors, visual sensors (i.e. cameras) are special because they can provide rich and versatile information. The world already has more than one billion cameras on mobile phones. We define the internet-working of visual sensors as the Internet of Video Things. This article estimates the number of cameras the world will see in 2030 and the implications of a large number of cameras. Transmitting, storing, and analyzing the data from cameras could impose significant challenges to existing technological infrastructures. This paper surveys recent progress in relevant technologies and suggests directions for future research.

Spectrum trading benefits secondary users (SUs) with accessing opportunities and primary users (PUs) with monetary gains in cognitive radio networks. In the spectrum trading market, bidding privacy is a serious concern for SUs, since untrustworthy PUs or spectrum traders may leverage bidding information to manipulate the trading or leak SU's bids to other SU competitors for illegal gains. Current centralized privacy preserving spectrum trading designs may incur extra infrastructure deployment, miss many instantaneous spectrum accessing opportunities, and have scalability issues. In this paper, we propose a novel privacy-preserving semi-distributed spectrum trading scheme, which has joint consideration of spectrum reuse, SUs' bidding privacy preservation, and PUs' revenue maximization. We use the conflict graph to characterize SUs' interference relationships, and jointly employ the Paillier Cryptosystem and dynamic matching with evolving preferences to conduct the privacy-preserving spectrum trading in a semi-distributed manner. Through security, complexity and performance analysis, we show that the proposed scheme can effectively preserve the privacy of SUs' bidding values, and notably increase the PUs' revenue and improve spectrum utilization with limited overhead.

On-demand wireless data broadcast is an efficient way to disseminate data to a large number of mobile users. In many applications, such as stock quotes and flight schedules, users may have to download multiple data items per request. However the multi-item request scheduling has not yet been thoroughly investigated for on-demand wireless data broadcasts. In this paper, we step-up on investigating this problem from viewpoint of theory and simulation. We develop a two-stage scheduling scheme to arrange the requested data items with the objective of minimizing the average access latency. The first stage is to select the data items to be broadcast in the next time period and the second stage is to schedule the broadcasting order for the data items selected in the first stage. We develop algorithms for the two stages respectively and analyze them both theoretically and practically. We also compare the proposed algorithms with other well known scheduling methods through simulation. The theoretical findings and simulation results reveal that significantly better access latency can be obtained by using our scheduling scheme rather than its competitors.

Mobile hotspots have made the dream of ubiquitous Internet access come true, while the widespread applications are still hindered by the limited power of smart phones. To address this issue, we propose a novel distributed cooperative data transmission scheme for energy-rechargeable mobile devices. In particular, we not only let a mobile phone help the nearby client devices connect to the Internet via its cellular accessing, but also let those clients replenish the mobile hotspot energy via wireless power transfer. We mathematically formulate the mutually beneficial relationship between mobile hotspots and clients into an optimization problem, with the objective of conducting the cooperative wireless data and energy transmission to maximize the system utility. Resorting to methods from combinatorics and matching theory, we develop a near optimal solution for many-to-one matching when there is a single mobile hotspot and a distributed matching strategy for the general case by considering the nature of data communication and the characteristic of wireless power transfer. By extensive simulation, we show that the proposed distributed solution achieves a performance close to the centralized method, and it outperforms the greedy matching strategy and the classic Gale-Shapley matching strategy in different scenarios.

Energy is the impediment to various applications of battery-powered wireless sensor networks (WSNs). Beyond the battery constraint of sensors/aggregation and forwarding nodes (AFNs), the major energy consumption of WSNs is from the longdistance multi-hop transmissions from the sensors/AFNs to the sink. To address these issues, in this paper, we employ a wireless charging vehicle (WCV) to travel inside WSNs to replenish the energy of sensors/AFNs, and cut long-distance transmissions into short-distance ones. Different from prior works, we let the WCV not only recharge the AFNs selectively, but also collect data from chosen AFNs and bring collected data back to the sink. The chosen AFNs play as virtual sinks, and nearby AFNs can use short-distance transmissions to deliver their traffic to the chosen AFNs. We formulate this problem into an energy replenishment optimization with joint consideration of sensed data delivery, flow routing, wireless power transfer, etc. Since the formulated problem is mixed integer nonlinear programming which is NP-hard to solve, we also develop a heuristic algorithm for feasible solutions. Through simulations, we show that the solution of the proposed algorithm is close to the optimal one and the energy replenishment is optimized while data delivery guaranteed.

Due to technological advances in micro-electronics, digital electronics, and wireless data communications, we have witnessed the advent of Wireless Sensor Networks (WSNs) and related applications in many areas such as battlefield surveillance, environmental monitoring, and biomedical observation. In this paper, we investigate the Maximum Directional Target Coverage Problem (MDTCP) for a special group of wireless sensor networks in which each sensor has a specific coverage range and a limited coverage angle. Given a set of sensors and a set of target points in a finite area, the objective of MDTCP is to cover the maximum number of target points by adjusting the directions of sensors. We develop a polynomial time approximation algorithm with performance ratio 1-e/e for MDTCP. In addition, we also analyze the structure of MDTCP from the Combinatorics' point of view.

Network lifetime is critical to any battery operated wireless sensor networks (WSNs). Especially for delay-sensitive WSNs, it's challenging to prolong the network lifetime while meeting the delay requirements of different applications. We investigate how to optimize the network lifetime of delay-sensitive WSNs with respect to energy efficient routing and sleep scheduling. Instead of treating routing and sleep scheduling as two separate approaches, we have a joint consideration of them, and mathematically formulate the lifetime maximization problem. Since the formulated problem is a mixed integer nonlinear programming (MINLP) problem and NP-hard to solve, we relax it into a linear programming (LP) problem and solve the relaxed problem for the upper bound. We also develop a heuristic algorithm-RSF for feasible solution, which yields a lower bound of WSNs' lifetime. Through extensive simulations, we show that the solution found by the proposed algorithm is close to the optimal one and the proposed scheme is effective in prolonging the lifetime of delay-sensitive WSNs.

Summary form only given. Data aggregation and active/sleep scheme are wildly used in energy-efficient wireless sensor networks. However, little research has been done on the optimal active/sleep scheme design for an aggregator node. In our previous work, we developed a stochastic model of aggregator node with active/sleep scheme for performance analysis and optimization. That model simulates the direct mode transfer from active to sleep or vice versa. In this paper, we propose a new stochastic analytical model for aggregator with multiple modes in the active period which reflect the wireless sensor's multiple energy saving modes. We derive Complete Aggregation Packet (CAP) rate, Total Aggregation Packet (TAP) rate, the Success Ratio which is defined as CAP rate divided by TAP rate, and Average Packet Delay (APD) to evaluate the aggregator performance. The extensive numerical simulations validate the accuracy of the stochastic analytical model. We would like to optimize the performance measures of APD and TAP rate by Lagrangian Optimization method which has not been finished yet.

Network lifetime is a critical design goal of any battery operated large scale wireless sensor networks (WSNs). In this paper, we investigate how to prolong the lifetime of large scale WSNs via optimal placement of base stations (BSs). With multiple BSs placed, the sensor nodes can send their data to nearby sinks and may reduce energy consumption of relaying packets for other sensor nodes. Due to the high cost of BSs and geographical constraints in WSNs, we can only place a limited number of BSs in a few candidate locations. Considering wireless transmission features and flow routing, we formulate this base station placement (BSP) problem in WSNs into a mixed integer nonlinear programming (MINLP) problem. In view of the NP-hardness of the formulated problem, we develop the heuristic algorithm to pursue feasible solutions. Through extensive simulations, we show that the solutions found by the proposed algorithm are close to the optimal one and the proposed scheme is effective in prolonging the lifetime of large scale WSNs.

Data aggregation and active/sleep scheme are frequently used methods in energy efficient wireless sensor networks. However, little research has been done on the optimal active/sleep scheme design for an aggregator node. In our previous work, we developed a stochastic model of an aggregator node with active/sleep scheme for performance analysis and optimization. That model simulates the direct mode transfer from active to sleep and vice versa. In this paper, we propose a new stochastic analytical model for an aggregator with multiple modes in the active period which reflect the wireless sensor's multiple energy saving modes. We derive the Complete Aggregation Packet (CAP) rate, the Total Aggregation Packet (TAP) rate, the Success Ratio which is defined as CAP rate divided by TAP rate, and the Average Packet Delay (APD) to evaluate the aggregator performance. By the Lagrangian Optimization method, we optimize APD under the constraint of the TAP rate. The extensive numerical simulations validate the accuracy of the analytical results.

This paper investigates the optimal call admission control (CAC) policy for non-priority scheme (NPS) and reserved channel scheme (RCS) in wireless networks, respectively. Both new call and handoff call arrival processes are assumed to be Poisson processes, and the call holding times are exponentially distributed with different rate for new call and handoff calls. Admitting each call would bring a reward to the network provider but holding each call in the system would also incur some expenses (or cost) to the provider. We concentrate on the optimization problems of when to admit or reject a call in order to achieve the maximum total expected discounted reward. By establishing a discounted Semi Markov Decision Process (SMDP) model, we verify that the optimal policies are state-related control limit policies for both NPS and RCS. Our numerical results explained in both tables and diagrams are consistent with our theoretic results.

In this paper, we propose the expected schedulability to characterize the schedulability for the stochastic tasks on a single real-time computer processor. Our results show that the stochastic model has more flexibility to characterize the real-time tasks than the deterministic model. The expected schedulability is related to the real-time t at tasks arrival and may show that a sub-set of task would be scheduled at any given real-time interval. The numerical analysis based on our theoretic results is consistent with the simulation analysis. Both numerical and simulation results show that the tasks would be scheduled for real-time tasks in realtime systems if the traffic load is less than a specific value which is more than 69%, which was provided in some deterministic situations. This observation implies that the expected schedulability based on the stochastic model would provide a bigger threshold for the real-time tasks to be scheduled.

In this paper, we investigate the call admission control (CAC) policy of a single cell in multimedia wireless networks with reservation channel scheme (RCS) for different classes of calls. Arrival process of each class of calls is assumed to be a Poisson process, the service time of each call is exponentially distributed. Admitting a call would bring a reward. However, if the reserved channels for the arriving call are all occupied, connecting this arriving call in the system will also bring a call holding cost per unit time. In order to achieve the maximum expected reward, we establish a discounted semi Markov decision process (SMDP) model and then derive the optimal policy for admitting or rejecting the arriving calls. We verify that the optimal CAC policy is a control limit policy if the cost functions have some special properties. Simulation result is consistence with the numerical result from our theoretic analysis.

This paper investigates the optimal call admission control (CAC) policy for the reserved channel schemes (RCS) in a wireless network. Under the assumption that all calls arrival processes are Poisson processes, their service times are exponentially distributed, admitting each call would bring a reward and there are holding costs per unit time, we figure out the optimal policy of when to reject the calls in order to achieve the maximum reward. A discounted semi Markov decision process (SMDP) model is used to derive the optimal policy for maximum total expected discounted reward on each state. We verified that the optimal CAC policy is a control limit policy if the cost functions have some special properties.

It is well known that the call admission policy has a big impact on the performance of a wireless network. Due to the nonlinear dependence between new calls and handoff calls, it becomes quite difficult to exactly model a wireless network. In this paper, we take all the incoming calls to a single cell of a wireless network as one class, their distribution as a general distribution and model it as a semi-Markov decision process (SMDP). Assuming that accepting each call would contribute a reward to the system and the system incurs a cost per unit time for the calls waiting in the buffer, we derive the optimal call admission control policy for the maximum reward. By using SMDP technique, we find that optimal call admission control policy is a control limit policy if the waiting cost function is a convex nondecreasing function.

In most analytical models for wireless cellular networks, the channel holding times for both new and handoff calls are usually assumed to be independent and identically distributed. However, simulation study and field data show that this assumption is invalid. In this paper, we present a new general analytical model in wireless cellular networks where channel holding times for new and handoff calls are distinctly distributed with different average values. For our proposed model, we first derive the explicit matrix product-form solution of the stationary probability for number of new and handoff calls in the system. We then show that the expression of the stationary probability for total number of calls in the system possesses a scalar product-form solution if and only if the expected channel holding times for both new and handoff calls are the same. Moreover, we derive analytical results for the blocking probabilities of new and handoff calls. Finally, we compare our new theoretical results with the corresponding simulation results and two already existing approximations. Through this comparison study, we show that our analytical results are indeed the same as the simulation results and that there are certainly significant estimation errors for the existing approximations.

Due to the inherent flexibility, scalability and reliability advantages of mesh networking architecture, the IEEE 802.16 working group is actively standardizing the mesh mode. Compared with the point-to-multipoint (PMP) mode, the newly introduced mesh mode has not specified any solution for providing quality-of-service (QoS) mechanisms in the literature. In this paper, a simple and effective scheme achieving QoS differentiation in the WiMAX mesh networking mode was proposed and analyzed. In addition, by taking account into the dynamics of networks topologies and also the variations of different protocols, a characteristics matrix for a mesh network from stochastic point of view was introduced. Based on the matrix, a new formula was developed for the performance metrics which enables the theoretical evaluation of a random topology. Illustrative numerical examples are presented to demonstrate the effectiveness of the proposed strategy, and also the impacts of the key parameters in differentiating the various services.

A novel call admission control (CAC) scheme for an adaptive heterogeneous multimedia mobile network with multiple classes of calls is investigated here. Different classes of calls may have different bandwidth requirement, different request call holding time and different cell residence time. At any time, each cell of the network has the capability to provide service to at least a given number of calls for each class of calls. Upon the arrival (or completion or hand off) of a call, a bandwidth degrade (or upgrade) algorithm is applied. An arriving call to a cell, finding insufficient bandwidth available in this cell, may either be disconnected from the network or push another call out of the cell toward a neighboring cell with enough bandwidth. We first prove that the stationary distribution of the number of calls in the network has a product form and then show how to apply this result in deriving explicit expressions of handoff rates for each class of calls, in obtaining the disconnecting probabilities for each class of new and handoff calls, and in finding the grade of service of this mobile network

Code division multiple-access (CDMA) schemes are widely used in cellular communications system because they provide high quality, reduced interference and result in high system capacity. In CDMA systems since one carrier frequency is being used, a phenomenon known as soft hand off occurs when a user changes radio resources from one base station to another. In this paper, we propose a soft hand off scheme using a two cell and roaming user probability approach, to properly illustrate the hand off process between the cells of interest. The proposed scheme assumes that calls entering the soft region are immediately assigned two channels. This assumption helps to reduce the blocking probability of new calls in the soft region as opposed to other schemes which do not explicitly cater for such calls. A three dimensional Markov process is created to describe and develop the stochastic behavior of the calls in the system. Performance measures such as new call blocking probability, hand off call blocking probability, channel efficiency, total carried traffic are deduced

An analytical traffic model and three queue management schemes are developed for a heterogeneous multihop mobile ad hoc network (MANET). The traffic model is built by a two-dimensional Markov process and some important performance metrics are developed. Based on the obtained metrics, three queue management schemes with QoS (quality of service) provisioning are developed for dynamic traffic conditions. Performance comparisons among the three schemes are presented

Recently mobile ad hoc networks (MANETs) are attracting increasing attention. Much work has been done by using various simulations tools. In this paper, we evaluate the performance of MANETs by analytic modeling. Based on two-dimensional Markov processes, several analytical models for packet traffic flow and connection availability are built by considering the impact of various types of failures. Some interesting performance metrics are then determined, e.g., steady state path availability (SSPA), mean end-to-end packet delay (EEPD), and loss of packets due to unavailability (LPU). The developed models and metrics are expected to serve as the first step for performance evaluation and guide for protocol design of MANETs

An analytical modeling method is developed for the evaluation of integrated 3G/WLAN networks. To adapt the feature of the emerging wireless networks efficiently and to cover many possible situations in reality, the cell residence times are modeled generally. The channel occupancy times, the horizontal and vertical handoff rates as well as some interesting performance measures are derived and calculated. Both analysis and numerical results show that the performance of the 3G network is significantly increased when the integrated 3G/WLAN network is employed, and that the performance of integrated 3G/WLAN network is improved greatly when the WLANs are in the hot-spot areas. The method developed here is expected to be useful for modeling and performance evaluation of other type of networks, such as the 3G network with the infrastructureless-mode WLANs or ad-hoc networks

The rapid growth of wireless services and mobile users drives a great interest in cellular networks with a hierarchical structure. Hierarchical cellular networks (HCNs) can provide high system capacity, efficient channel utilization and inherent load-balancing capability. In this paper, a two-layer hierarchical cellular network with bidirectional overflow and take-back strategies under generally distributed cell residence times is considered. An analytical model and a performance analysis method are developed, and a number of important performance measures are evaluated. The developed model and analysis method can be easily extended to multi-layer HCNs

This paper presents a new channel allocation scheme with preemptive priority for the integrated voice/data mobile network. Based on the scheme, a two-dimensional Markov process is built, and the steady-state probability is solved by the matrix-analytic method. The preemptive priority mechanism introduced gives more benefit to voice traffic at the expense of degrading some data traffic, while the victim buffer compensates the degradation and has no negative effect on voice traffic. From the analysis and numerical results, we can conclude that our scheme can guarantee different QoS requirements from different traffic classes, and significantly improve the channel utilization.

This paper presents an analytical model of adaptive bandwidth allocation scheme, called complete sharing with preemptive priority (CSPP) scheme, for multi-service wireless cellular networks. It employs movable boundaries to consider distinguishing the performance between multiple services, and uses the complete sharing approach to maximize the bandwidth utilization. Besides, the CSPP scheme captures the elastic data traffic by using a degradation/compensation mechanism and considers preemptive priority (PP) mechanism for voice traffic, while the degradation of data traffic by PP mechanism is compensated through a victim buffer. The analysis and numerical results demonstrate that our scheme can guarantee different QoS requirements from different traffic classes and improve the bandwidth utilization efficiency.

In this paper we use a WCDMA network simulator to evaluate the different performance criteria. We also simulate a transmit diversity scheme and use the results of the diversity scheme in the simulator to evaluate the QoS (quality of service) enhancements obtained. Further we explore the possibility of a coexistence of a WCDMA network with the WIPAS (wireless IP access system).

In this paper, we study a cellular mobile communications network with multiple cells and multiple classes of calls. The different classes of calls have different call holding times and residence time distributions. We consider a protocol mechanism under which a blocked call in a cell is either disconnected from the network or is deemed as a handoff call in a neighboring cell. Under this protocol, we prove that the stationary distribution of this cellular mobile network has a product form. This allows us to derive explicit expressions for handoff rates of each class of calls from one cell to another and the disconnecting probabilities for each class of new and handoff calls. Our numerical results show how these measures depend on the mobility of the mobile terminals in each cell and on the numbers of reserved channels.

This paper presents an analytical model of channel allocations with preemptive priority to study the handoff performance for integrated voice/data mobile networks. By analyzing the system as a quasi-birth-and-death process, we obtain the steady state probabilities and some interesting performance measures, such as new voice (new data) blocking probability, handoff voice (handoff data) dropping probability, the channel utilization, and the busy period time in the cell. From the analysis and numerical results, we can conclude that our scheme can provide complete service differentiation and different QoS guarantee for different traffic classes, and get pretty good channel utilization by appropriate threshold parameter design. The performance measures obtained in the paper are very useful in evaluating the needed resource of future wireless mobile networks.

In this paper, we study a cellular mobile communications network with multiple cells and multiple classes of calls. The different classes of calls have different call holding time and residence time distributions. We consider a protocol mechanism under which a blocked coil in a cell is either disconnected from the network or is deemed as a handoff call in a neighboring cell. Under this protocol, we prove that the steady state probability of this cellular mobile network has a product form. This allows as to derive explicit expressions of handoff rates for each class of calls from one cell, to another and the disconnecting probabilities for each class of new and handoff calls. Our numerical results show how these measures depend on the mobility of the mobile terminals in each cell and on the numbers of reserved channels, respectively.

Motivated from analytic models of wireless mobile system where there are new calls and handoff calls in each cell, we consider a general model with two different types of calls in this paper. The key difference here from the existing wireless models are that (1) the different types of calls possess different call holding time and different cell residence time and (2) one type of calls has the priority over another type of calls from the viewpoint of reservation and an available buffer. More detailed differences between the existing models and the proposed model in novelty are stated. For the proposed model, the state process governing the system is verified to be a quasi-birth-and-death process and the transition rate matrix of this process is explicitly derived. Furthermore, the closed formulae of the blocking probabilities for each types of calls are obtained, the blocking periods for each types of calls are verified to be phase type distributions and the corresponding distributions are explicitly derived.

An analytic model of cellular mobile communications networks with instantaneous movement is investigated in this paper. This cellular mobile network is showed to be equivalent to a queueing network and furthermore the equilibrium distribution of this cellular mobile network is proved to have a product form. The explicit expressions for handoff rates of calls from one cell to another, the blocking probability of new calls and handoff calls are then obtained. Actual call connection time (ACCT) of a call in this cellular mobile network is characterized in detail, which is the total time a mobile user engages in communications over the network during a call connection and can be used to design appropriate charging schemes. The average ACCT for both complete call and incomplete call, as well as the probability for a call to be incomplete or complete, are derived. Our numerical results show how the above measures depend on the new call arrival process for some specific reserved channels numbers in each cell. The results presented in this paper are expected to be useful for the cost analysis for updating location and paging in cellular mobile network.

A novel network allocation scheme of wireless mobile communications networks is investigated in this paper. We study the handoff rates of calls from one cell to another and obtain the blocking probabilities for new calls and handoff calls. Actual call connection time (ACCT) of a call is investigated, which is the total time a mobile user engaged in communications over a wireless network during a call connection and can be used to design appropriate charging schemes. Our numerical results show that how these measures depend on the new call arrival rate with specific reserved channels for handoff calls in each cell. These results are expected to be useful for the cost analysis for updating location and paging in wireless mobile network.

In this paper, the arrival of new calls and handoff calls to a personal communications services (PCS) network is modeled by a Markov arrival process (MAP) in which we allow correlation of the interarrival times among new calls, among handoff calls, as well as between these two kinds of calls. A new call will retry again if the first attempt is blocked. The PCS network consists of homogeneous cells and each cell consists of a finite number of channels. Under the general conditions that all random variables involved have general phase type (PH) distribution, we develop an explicit expression of the infinitesimal generator matrix of the Markov chain governing the network and find its complexity. This hits been a difficult matrix to obtain, judging from the works in the literature. It is very complex to develop and has not been previously obtained by other researchers. Some methods to find the stationary probability of the network are discussed. Particularly, we introduce an effective method, from which we can obtain the new call blocking probability and the handoff call failure probability. Also, the busy period of the orbit is introduced. This is an interesting measure from the viewpoint of network provider; its distribution and expectation are then obtained. The results presented in this paper can be used to provide some guidelines to performance evaluation for PCS network design.

Actual call connection time (ACCT) is the total time that a mobile user engages in communications over a wireless network during a call connection. Due to limited network resources of wireless mobile networks, a call connection may be prematurely disconnected and the ACCT for the call in general may not be the same as the requested call connection time (RCCT). The ACCT depends not only on the RCCT, but also on the network resource allocation scheme and network traffic. We characterize the ACCT and related performance metrics for wireless mobile networks under a newly proposed general channel allocation scheme. This scheme generalizes the nonprioritized scheme, the reserved channel scheme, the queueing priority scheme and the subrating scheme in such a way as to reduce the blocking probability of the handoff calls while keeping the ACCT as long as possible. Explicit formulae for the distribution and the expectation of the ACCT are obtained. The call completion probability, the call drop probability, and the average actual call connection times for both the complete calls and the incomplete calls are derived. The results can form the basis for designing better billing rate schemes by differentiating incomplete calls and complete calls.

The 64-bit Intel® Itanium™ architecture is designed for high-performance scientific and enterprise computing, and the Itanium processor is its first silicon implementation. Features such as extensive arithmetic support, predication, speculation, and explicit parallelism can be used to provide a sound infrastructure for supercomputing. A large number of high-performance computer companies are offering Itanium™-based systems, some capable of peak performance exceeding 50 GFLOPS. In this paper we give an overview of the most relevant architectural features and provide illustrations of how these features are used in both low-level and high-level support for scientific and engineering computing, including transcendental functions and linear algebra kernels.

This paper studies the quasi-waiting time, the actual waiting time of the handoff calls in the buffer and the actual call holding times of new calls for the mobile wireless networks, in which the new calls arrival processes may depend on the number of calls in the target cells and the handoff calls arrival processes from the given cell to the target cell are modeled to be dependent on the number of calls in the given cells. In particular, the caller in the buffer waiting for further communication may become impatient. We propose an analytical model and obtain the expressions of the quasi and actual waiting time of a handoff call in the buffer, and prove that the actual call holding time of a new call is exponential. Some special cases of our model used in previous traffic models of wireless and/or wireline communications are discussed. The results presented in this paper may provide guidelines for field data processing on updated wireless mobile network design and performance evaluation.

This paper studies the behavior for performance evaluation of a personal communication services (PCS) network, in which the handoff call arrival processes and the new call arrival processes may depend on the number of calls in the target cells, and the caller may become impatient. We propose an analytical model and obtain the expressions of some interesting conventional and some new performance measures. Many special cases of our model used in previous traffic models of wireless and/or wireline communications are discussed. The results presented in this paper can provide guidelines for field data processing on updated PCS network design and performance evaluation.

The arrival of calls (i.e., new and handoff calls) in a personal communications services (PCS) network are modeled by a Markov arrival process (MAP) in which we allow correlation of the interarrival times among new calls, among handoff calls, as well as between these two kinds of calls. Each cell of the network consists of a finite number of channels and a buffer with finite size for handoff calls. There exist some channels among each cell which can be used by splitting the original rate into two channels with different rates if necessary when a handoff call arrives and finds all the channels busy. We obtain the stationary joint probability of number of calls in the cell and the phase of the arrival process, the blocking probability of a new call, the forced termination probability of a handoff call, and the mean dwell time of a handoff call in the buffer. Finally, we obtain the distribution and the mean of the cell's busy period, the distribution and the mean of the first time to split the cth channel, and some other interesting performance measures for the network. Some explicit results for special cases obtained by Lin et al. (see IEEE Trans. Vech. Technol., vol.45, no.1, p.122-30, 1996 and vol.43, no.3, p.704-12, 1994), Tekinary et al. (1992) and by Yoon et al. (1993) can also be directly obtained from the general conclusion. The results presented can provide guidelines for field data processing in PCS network design and performance evaluation.

The explicit distribution function of the actual holding time of a new call in a PCS network, with general cell residence time and general requested call holding time, is obtained. The effective call holding time of an incompleted and of completed calls are shown to be the conditional actual holding time of an incompleted call and of a completed call, respectively. If the holding time is of Erlang or if both the residence and requested call holding times belong to the class of new better than used (NBU), we proved that the mean effective call holding time of an incompleted call is less than the mean requested call holding time of a call. For any kind of random variables of the residence time and requested call holding time, we proved that the mean effective call holding time of a completed call is always less than the mean requested call holding time of a call.