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A locally repairable code with availability has the property that every code symbol can be recovered from multiple, disjoint subsets of other symbols of small size. In particular, a code symbol is said to have $(r,t)$-availability if it can be recovered from $t$ disjoint subsets, each of size at most $r$. A code with availability is said to be 'rate-optimal', if its rate is maximum among the class of codes with given locality, availability, and alphabet size. This paper focuses on rate-optimal binary, linear codes with small availability, and makes four contributions. First, it establishes tight upper bounds on the rate of binary linear codes with $(r,2)$ and $(2,3)$ availability. Second, it establishes a uniqueness result for binary rate-optimal codes, showing that for certain classes of binary linear codes with $(r,2)$ and $(2,3)$-availability, any rate optimal code must be a direct sum of shorter rate optimal codes. Third, it presents novel upper bounds on the rates of binary linear codes with $(2,t)$ and $(r,3)$-availability. In particular, the main contribution here is a new method for bounding the number of cosets of the dual of a code with availability, using its covering pr

Availability analysis is used to assess the possible failures and their restoration process for a given system. This analysis involves the calculation of instantaneous and steady-state availabilities of the individual system components and the usage of this information along with the commonly used availability modeling techniques, such as Availability Block Diagrams (ABD) and Fault Trees (FTs) to determine the system-level availability. Traditionally, availability analyses are conducted using paper-and-pencil methods and simulation tools but they cannot ascertain absolute correctness due to their inaccuracy limitations. As a complementary approach, we propose to use the higher-order-logic theorem prover HOL4 to conduct the availability analysis of safety-critical systems. For this purpose, we present a higher-order-logic formalization of instantaneous and steady-state availability, ABD configurations and generic unavailability FT gates. For illustration purposes, these formalizations are utilized to conduct formal availability analysis of a satellite solar array, which is used as the main source of power for the Dong Fang Hong-3 (DFH-3) satellite.

In this paper we investigate bounds on rate and minimum distance of codes with $t$ availability. We present bounds on minimum distance of a code with $t$ availability that are tighter than existing bounds. For bounds on rate of a code with $t$ availability, we restrict ourselves to a sub-class of codes with $t$ availability called codes with strict $t$ availability and derive a tighter rate bound. Codes with strict $t$ availability can be defined as the null space of an $(m \times n)$ parity-check matrix $H$, where each row has weight $(r+1)$ and each column has weight $t$, with intersection between support of any two rows atmost one. We also present two general constructions for codes with $t$ availability.

The move towards the microservice based architecture is well underway. In this architectural style, small and loosely coupled modules are developed, deployed, and scaled independently to compose cloud-native applications. However, for carrier-grade service providers to migrate to the microservices architectural style, availability remains a concern. Kubernetes is an open source platform that defines a set of building blocks which collectively provide mechanisms for deploying, maintaining, scaling, and healing containerized microservices. Thus, Kubernetes hides the complexity of microservice orchestration while managing their availability. In a preliminary work we evaluated Kubernetes, using its default configuration, from the availability perspective in a private cloud settings. In this paper, we investigate more architectures and conduct more experiments to evaluate the availability that Kubernetes delivers for its managed microservices. We present different architectures for public and private clouds. We evaluate the availability achievable through the healing capability of Kubernetes. We investigate the impact of adding redundancy on the availability of microservice based applic

Cloud computing has achieved great success in modern IT industry as an excellent computing paradigm due to its flexible management and elastic resource sharing. To date, cloud computing takes an irrepalceable position in our socioeconomic system and influences almost every aspect of our daily life. However, it is still in its infancy, many problems still exist.Besides the hotly-debated security problem, availability is also an urgent issue.With the limited power of availability mechanisms provided in present cloud platform, we can hardly get detailed availability information of current applications such as the root causes of availability problem,mean time to failure, etc. Thus a new mechanism based on deep avaliability analysis is neccessary and benificial.Following the prevalent terminology 'XaaS',this paper proposes a new win-win concept for cloud users and providers in term of 'Availability as a Service' (abbreviated as 'AaaS').The aim of 'AaaS' is to provide comprehensive and aimspecific runtime avaliabilty analysis services for cloud users by integrating plent of data-driven and modeldriven approaches. To illustrate this concept, we realize a prototype named 'EagleEye' with al

This paper studies the problem of code symbol availability: a code symbol is said to have $(r, t)$-availability if it can be reconstructed from $t$ disjoint groups of other symbols, each of size at most $r$. For example, $3$-replication supports $(1, 2)$-availability as each symbol can be read from its $t= 2$ other (disjoint) replicas, i.e., $r=1$. However, the rate of replication must vanish like $\frac{1}{t+1}$ as the availability increases. This paper shows that it is possible to construct codes that can support a scaling number of parallel reads while keeping the rate to be an arbitrarily high constant. It further shows that this is possible with the minimum distance arbitrarily close to the Singleton bound. This paper also presents a bound demonstrating a trade-off between minimum distance, availability and locality. Our codes match the aforementioned bound and their construction relies on combinatorial objects called resolvable designs. From a practical standpoint, our codes seem useful for distributed storage applications involving hot data, i.e., the information which is frequently accessed by multiple processes in parallel.

The widespread use of publicly available datasets for training machine learning models raises significant concerns about data misuse. Availability attacks have emerged as a means for data owners to safeguard their data by designing imperceptible perturbations that degrade model performance when incorporated into training datasets. However, existing availability attacks are ineffective when only a portion of the data can be perturbed. To address this challenge, we propose a novel availability attack approach termed Parameter Matching Attack (PMA). PMA is the first availability attack capable of causing more than a 30\% performance drop when only a portion of data can be perturbed. PMA optimizes perturbations so that when the model is trained on a mixture of clean and perturbed data, the resulting model will approach a model designed to perform poorly. Experimental results across four datasets demonstrate that PMA outperforms existing methods, achieving significant model performance degradation when a part of the training data is perturbed. Our code is available in the supplementary materials.

The need for high availability (HA) and disaster recovery (DR) in IT environment is more stringent than most of the other sectors of enterprises. Many businesses require the availability of business-critical applications 24 hours a day, seven days a week, and can afford no data loss in the event of a disaster. It is vital that the IT infrastructure is resilient with regard to disruption, even site failures, and that business operations can continue without significant impact. As a result, DR has gained great importance in IT. Clustering of multiple industries standard servers together to allow workload sharing and fail-over capabilities is a low cost approach. In this paper, we present the availability model through Semi-Markov Process (SMP) and also analyze the difference in downtime of the SMP model and the approximate Continuous Time Markov Chain (CTMC) model. To acquire system availability, we perform numerical analysis and SHARPE tool evaluation.

Multi-access Edge Computing (MEC) is one of the enabling technologies of the fifth generation (5G) of mobile networks. MEC enables services with strict latency requirements by bringing computing capabilities close to the users. As with any new technology, the dependability of MEC is one of the aspects that need to be carefully studied. In this paper, we propose a two-level model to compute the availability of a 5G-MEC system. We then use the model to evaluate the availability of a 5G-MEC system under various configurations. The results show that having a single redundancy of the 5G-MEC elements leads an acceptable availability. To reach a high availability, the software failure intensity of the management elements of 5G and MEC should be reduced.

High availability has always been one of the main problems for a data center. Till now high availability was achieved by host per host redundancy, a highly expensive method in terms of hardware and human costs. A new approach to the problem can be offered by virtualization. Using virtualization, it is possible to achieve a redundancy system for all the services running on a data center. This new approach to high availability allows to share the running virtual machines over the servers up and running, by exploiting the features of the virtualization layer: start, stop and move virtual machines between physical hosts. The system (3RC) is based on a finite state machine with hysteresis, providing the possibility to restart each virtual machine over any physical host, or reinstall it from scratch. A complete infrastructure has been developed to install operating system and middleware in a few minutes. To virtualize the main servers of a data center, a new procedure has been developed to migrate physical to virtual hosts. The whole Grid data center SNS-PISA is running at the moment in virtual environment under the high availability system. As extension of the 3RC architecture, several

High availability has always been one of the main problems for a data center. Till now high availability was achieved by host per host redundancy, a highly expensive method in terms of hardware and human costs. A new approach to the problem can be offered by virtualization. Using virtualization, it is possible to achieve a redundancy system for all the services running on a data center. This new approach to high availability allows the running virtual machines to be distributed over a small number of servers, by exploiting the features of the virtualization layer: start, stop and move virtual machines between physical hosts. The 3RC system is based on a finite state machine, providing the possibility to restart each virtual machine over any physical host, or reinstall it from scratch. A complete infrastructure has been developed to install operating system and middleware in a few minutes. To virtualize the main servers of a data center, a new procedure has been developed to migrate physical to virtual hosts. The whole Grid data center SNS-PISA is running at the moment in virtual environment under the high availability system.

A fundamental concept of the quantum Internet is quantum entanglement. In a quantum Internet scenario where the legal users of the network have different priority levels or where a differentiation of entanglement availability between the users is a necessity, an entanglement availability service is essential. Here we define the entanglement availability differentiation (EAD) service for the quantum Internet. In the proposed EAD framework, the differentiation is either made in the amount of entanglement with respect to the relative entropy of entanglement associated with the legal users, or in the time domain with respect to the amount of time that is required to establish a maximally entangled system between the legal parties. The framework provides an efficient and easily-implementable solution for the differentiation of entanglement availability in experimental quantum networking scenarios.

Spot instances offer significant cost savings of up to 90% over on-demand prices, making them an attractive resource for large-scale computing workloads. However, understanding their availability dynamics is essential for building systems that tolerate interruptions, and observing this availability directly requires keeping instances running, which incurs costs that scale with the number of monitored instance types and their per-instance price. We propose Spot-and-Scoot (SnS), a cost-efficient method that collects spot instance availability signals by leveraging the cloud provider's provisioning lifecycle. Since the outcome of a spot request is determined before the instance enters the running state, SnS submits requests and cancels them upon provisioning acceptance, collecting binary availability signals at near-zero instance cost. Submitting multiple concurrent requests per measurement point further yields a quantitative estimate of available capacity. We validate SnS through simultaneous collection of probing signals and actual running instance traces across 68 instance types and 15 regions on both AWS and Azure, totaling 336,033 spot requests. Analysis of 2,635 real-world inter

In this work, we introduce maximally recoverable codes with locality and availability. We consider locally repairable codes (LRCs) where certain subsets of $ t $ symbols belong each to $ N $ local repair sets, which are pairwise disjoint after removing the $ t $ symbols, and which are of size $ r+δ-1 $ and can correct $ δ-1 $ erasures locally. Classical LRCs with $ N $ disjoint repair sets and LRCs with $ N $-availability are recovered when setting $ t = 1 $ and $ t=δ-1=1 $, respectively. Allowing $ t > 1 $ enables our codes to reduce the storage overhead for the same locality and availability. In this setting, we define maximally recoverable LRCs (MR-LRCs) as those that can correct any globally correctable erasure pattern given the locality and availability constraints. We provide three explicit constructions, based on MSRD codes, each attaining the smallest finite-field sizes for some parameter regime. Finally, we extend the known lower bound on finite-field sizes from classical MR-LRCs to our setting.

Control systems behavior can be analyzed taking into account a large number of parameters: performances, reliability, availability, security. Each control system presents various security vulnerabilities that affect in lower or higher measure its functioning. In this paper the authors present a method to assess the impact of security issues on the systems availability. A fuzzy model for estimating the availability of the system based on the security level and achieved availability coefficient (depending on MTBF and MTR) is developed and described. The results of the fuzzy inference system (FIS) are presented in the last section of the paper.

In current presence or availability systems, the method of presenting a user's state often supposes an instantaneous notion of that state - for example, a visualization is rendered or an inference is made about the potential actions that might be consistent with a user's state. Drawing on observational research on the use of existing communication technology, we argue (as have others in the past) that determination of availability is often a joint process, and often one that takes the form of a negotiation (whether implicit or explicit). We briefly describe our current research on applying machine learning to infer degrees of conversational engagement from observed conversational behavior. Such inferences can be applied to facilitate the implicit negotiation of conversational engagement - in effect, helping users to weave together the act of contact with the act of determining availability.

The best way to design a network is to take into account Availability values and Capacity Planning. You already saw Availability expressed with numbers such as 99.99%. The purpose of this document is to introduce the way to compute Availability values using Reliability Block Diagrams.

In many markets buyers are poorly informed about which firms sell the product (product availability) and prices, and therefore have to spend time to obtain this information. In contrast, sellers typically have a better idea about which rivals offer the product. Information asymmetry between buyers and sellers on product availability, rather than just prices, has not been scrutinized in the literature on consumer search. We propose a theoretical model that incorporates this kind of information asymmetry into a simultaneous search model. Our key finding is that greater product availability may harm buyers by mitigating their willingness to search and, thus, softening competition.

The $i$th coordinate of an $(n,k)$ code is said to have locality $r$ and availability $t$ if there exist $t$ disjoint groups, each containing at most $r$ other coordinates that can together recover the value of the $i$th coordinate. This property is particularly useful for codes for distributed storage systems because it permits local repair and parallel accesses of hot data. In this paper, for any positive integers $r$ and $t$, we construct a binary linear code of length $\binom{r+t}{t}$ which has locality $r$ and availability $t$ for all coordinates. The information rate of this code attains $\frac{r}{r+t}$, which is always higher than that of the direct product code, the only known construction that can achieve arbitrary locality and availability.

Software-defined networking (SDN) promises to improve the programmability and flexibility of networks, but it may bring also new challenges that need to be explored. The purpose of this technical report is to assess how the deployment of the SDN controllers affects the overall availability of SDN. For this, we have varied the number, homing and location of SDN controllers. A two-level modelling approach that is used to evaluate the availability of the studied scenarios. Our results show how network operators can use the approach to find the optimal cost implied by the connectivity of the SDN control platform by keeping high levels of availability.