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With the surge in online education, more universities have shifted classes online. The growing popularity of MOOC courses and the changing education landscape could mean more and more people switching to online education. A primary drawback is the difficulty in monitoring of students during an online examination which leads to a lot of malpractices used by candidates. This paper explores computer vision based techniques to propose a five-fold proctoring mechanism for online tests. The features incorporated are authentication, head movement, eye motion tracking, speech detection and object detection. The solution has an overall accuracy of 91% accuracy.

Memory-mapped I/O (mmio) is emerging as a viable alternative for accessing directly-attached fast storage devices compared to explicit I/O with system calls. Mmio removes the need for costly lookups in the DRAM I/O cache for cache hits, as they are handled in hardware via the virtual memory mechanism. In this work we present HugeMap, a custom mmio path in the Linux kernel that uses huge pages for file-backed mappings to accelerate applications with sequential I/O access patterns or large I/O operations. HugeMap uses huge pages to reduce CPU processing in the kernel I/O path compared to regular mmap. We explore the benefits and trade-offs of huge pages in HugeMap using microbenchmarks, IOR, and an in-house persistent key-value store designed for mmio. Our experiments show up to \(3.7\times \) higher throughput and up to \(4.76\times \) lower system time, compared to regular page configurations.

We consider a retrial queueing system with limited processor sharing which can be used for modeling the operation of a cell of fixed capacity in a wireless cellular network with two types of customers (handover and new customers). Customers of two types arrive at the system according to the Marked Markovian Arrival Process (MMAP). Arriving customers of each type follow a bandwidth sharing policy. In period when the number of customers of definite type in the system exceeds a threshold (different between new and handover customers) newly arriving customers of one type (handover customers) are considered to be lost while the customers of another type (new customers) go to orbit of infinite size. From the orbit, they try their attempts to reach a server in exponentially distributed time.

In this paper, we consider a single-server queueing inventory model with two types of customers, say, type-1 and type-2. The queue formed by the type-1 customer is infinite. The queue formed by the type-2 customer can accommodate a maximum of N customers. Even though the same server provides service to both types of customers, type-1 customers are served one by one, while type-2 customers are served in batches of varying sizes. The service is initiated only when inventory is available and the service time is assumed to be positive. If at least one item is available in the inventory and the server is idle, an arriving type-1 customer can directly enter into the service. The service of the type-2 customer is initiated either upon realization of a random clock that started ticking with the arrival of the first type-2 customer or by the accumulation of N type-2 customers, whichever occurs first. The arrivals follow a Marked Markovian process. Service time distribution of both type-1 and type-2 customers follow two different phase-type distribution. Replenishment of inventory follows the (s, S) policy having a positive lead time. It is assumed that N is less than s. Steady-state analysis, as well as evaluation of some performance measures, have been done. The model is analyzed numerically and graphically.

We consider a single-server queueing system with two parallel queues of which one is a finite buffer for priority customers and the other infinite for ordinary customers. Two types of customers arrive according to the Marked Markovian Arrival Process (MMAP). Service times are assumed to follow phase-type distributions. A customer gets priority either by paying a cost or by any other means. Priority customers receive service on the basis of a token system which works according to the following rule: \(K-1\) lower priority customers are served consecutively, and the \( K^{th}\) one is from the priority queue, if there is any. Priority customers have the right to take the strategic decision in choosing the queue on arrival, if such a customer joins an ordinary queue then he loses the special benefit that he would have got otherwise. We introduce the joining strategy for the priority customers and call it ‘K-policy’ along with probabilistic decision whether to give up their additional benefit (reward). Steady-state analysis of the model is done. Some system characteristics are evaluated, a social optimization problem is discussed and numerical illustrations are provided.

We consider a single server retrial queueing system with parallel queues of ordinary and priority customers. Priority customers join the queues according to a probabilistic joining strategy until the ordinary queue is full. We also assume that there is a waiting room for the blocked ordinary customers and they make retrials from there, to enter into the ordinary queue. Priority customers on arrival, seeing both ordinary and priority queue as full loss the system forever. Customers receive service on the basis of a token system. Ordinary customers, upon arrival finding the ordinary queue as full, enter into the orbit. Ordinary customers make their retrials from the orbit in an exponential duration of time intervals to enter into the ordinary queue. Ordinary customer from the orbit make their retrials in an exponential duration of time intervals. Whenever the queue size of ordinary queue is less than N then the ordinary customer in the orbit successfully enter into the ordinary queue. Two types of customers arrive according to Marked Markovian Arrival Process (MMAP). Service times are assumed to follow phase type distributions. Steady-state analysis of the model is done. Some system characteristics are evaluated.

In this paper, we analyze a queueing system with two main unreliable servers and backup reliable server. The input flow is defined by the BMAP (Batch Markovian Arrival Process). Heterogeneous breakdowns arrive to the main servers according to a MMAP (Marked Markovian Arrival Process). Service times and repair times have PH (Phase type) distribution. The queueing system under consideration is an adequate model of operation of hybrid communication systems which combine the use of Free Space Optics and radio technologies. We derive a condition for the stable operation of the system, compute its stationary distribution and the key performance measures. Illustrative numerical examples give some insight into the behavior of the system.

In the present paper, the infinite-server queue model \(MMAP_{k}(t)|G_{k}|\infty \) in transient MMAP random environment with time varying marked MAP arrival of k types of customers subject to catastrophes is considered. The transient joint probability generating functions (PGF) of the number of different types of customers present in the model at moment t and the number of different types of customers departing from the system in the time interval (0, t] are found. The Laplace-Stieltjes transform (LST) of total volume of customers being in service at moment t is defined. The basic differential equations for joint probability generating functions of the number of busy servers and served customers for transient and stationary random environment are obtained.

We consider a tandem queueing network with two service stations without buffers. An infinite capacity station named as the main station provides usual paid service. Another station is a finite capacity station named as the offer zone. The offer zone is an intermediate station strategically designed to attract the maximum number of customers to the main station. The offer zone works under various random environments. Sojourn times of each random environment follows Phase Type distribution. Two types of customers arrive to the system according to an MMAP. Service times of customers at both the stations are exponentially distributed. The stationary probability distribution of the states of the Markov chain representing the proposed model is computed. Some operational and probabilistic characteristics of the system are determined. A control problem is discussed. A cost function is proposed. The effect of the maximum capacity of the offer zone on various performance measures are considered. Numerical as well as graphical illustrations are given.

With the widespread adoption of multicore chips, many multithreaded applications based on the shared address space have been developed. Widely-used operating systems, such as Linux, use a per-process lock to synchronize page faults and memory mapping operations (e.g., mmap and munmap) on the shared address space between threads, restricting the scalability and performance of the applications. We propose a novel Pthreads-compatible multithreaded model, PAthreads, which provides isolated address spaces between threads to avoid contention on address space, and meanwhile preserves the shared variable semantics. We prototype PAthreads on Linux by using a proposed character device driver and a proposed shared heap allocator IAmalloc. Pthreads applications can run with PAthreads without any modifications. Experimental results show that PAthreads runs 2.17\(\times \), 3.19\(\times \) faster for workloads hist, dedup on 32 CPU cores, and 8.15\(\times \) faster for workload lr on 16 cores than Pthreads. Moreover, by using Linux Perf, we further analyze critical bottlenecks that limit the scalability of workloads programmed by Pthreads. This paper also reviews the performance impact of the latest Linux 4.10 kernel optimization on PAthreads and Pthreads, and results show that PAthreads still has advantage for dedup and lr.

In the present paper the infinite-server \(MMAP_k|G_k|\infty \) queueing model with random resource vector of customers, marked MAP arrival and semi-Markov (SM) arrival of catastrophes is considered. The joint generating functions (PGF) of transient and stationary distributions of number of busy servers and numbers of different types served customers, as well as Laplace transformations (LT) of joint distributions of total accumulated resources in the model at moment and total accumulated resources of served customers during time [0, t) interval are found. The basic differential and renewal equations for transient and stationary PGF of queue sizes of customers are found.

A tandem retrial queueing system with orbital search in which two self-service stations namely, the main station and the offer zone and an orbit for passive customers lost from the offer zone without joining the main station is considered. The main service station is of infinite capacity while the offer zone which works in a random environment and the orbit for passive customers are of finite capacities. Two types of customers arrive to the service stations according to a Marked Markovian Arrival Process (MMAP) with representation \((D_0,D_1,D_2).\) The service times in both stations are exponentially distributed. A virtual search mechanism associated with the main station will be working when the number of customers in the main station is below a pre-assigned level L. The duration of search is exponentially distributed. The condition for system stability is established. The system state distribution in the steady state is obtained. Several system performance characteristics are derived. An associated optimization problem is investigated.

A complex multi-state system subject to different types of failures and preventive maintenance, with loss of units, is modelled by considering a discrete marked Markovian arrival process. The system is composed of K units, one online and the rest in cold standby. The online unit is submitted to different types of failures and when a non-repairable failure occurs the corresponding unit is removed. Several internal degradation states are considered which are observed when a random inspection occurs. This unit is subject to internal repairable failure, external shocks and preventive maintenance. If one internal repairable failure occurs, the unit goes to the repair facility for corrective repair, if a major degradation level is observed by inspection, the unit goes to preventive maintenance and when one external shock happens, this one may produce an aggravation of the internal degradation level, cumulative external damage or external extreme failure (non-repairable failure). Preventive maintenance and corrective repair times follow different distributions. The system is modelled in transient regime and relevant performance measures are obtained. All results are expressed in algorithmic and computational form and they have been implemented computationally with MATLAB and R. A numerical example shows the versatility of the model.

The article is devoted to the application of Markov modulated arrival processes (Markov modulated Poisson process — MMPP, Markov modulated Bernoulli process — MMBP and Markov modulated fluid flow — MMFF) models to the analysis of Active Queue Management (AQM) algorithms (Random Early Detection (RED) family, for example). The main ideas and properties of Markov modulated arrival processes (MMAP) are presented as the brief description of RED-type AQM algorithms. A review of the main results obtained with the help of MMAP processes in the analysis of AQM algorithms models is made. The authors formulated problems that also can be solved with the help of MMAP processes when analysing the systems with RED-like algorithms.

In this paper, a tandem queue consisting of two multi-server stations without buffers is investigated. Customers of two different types arrive to the first station in accordance with MMAP (Marked Markovian Arrival Process). The first type customers are satisfied with service at the first station only while the second type customers should be served successively at both stations. The system is studied in steady state. The stationary distribution of the system is calculated. A number of useful performance measures is derived. Decomposition and optimization problems are discussed.

AspectM is an aspect-oriented modeling language for providing not only basic modeling constructs but also an extension mechanism called metamodel access protocol (MMAP) that allows a modeler to modify the metamodel. This paper proposes a concrete implementation for constructing an aspect-oriented modeling environment in terms of extensibility. The notions of edit-time structural reflection and extensible model weaving are introduced.