Inter-process communication in MVS/XA and applications for scientific and engineering information processing

This paper surveys inter-process communication in MVS/XA (multiple virtual system/extended architecture) and explores the use of cross-memory services for this purpose. The lack of high-level interfaces to system services is a major handicap in MVS/XA. Tools to provide high-level services, in particular, tools for inter-process communication, can be implemented in a simple, elegant and efficient way. The implementation and use of a communication subsystem, the extended communication facility (ECF), are also described. The ideas and mechanisms presented are useful for many scientific and engineering applications running under MVS/XA. Examples include distributed systems, applications using concurrent programming, a quasi-batch environment, communication subsystems, and mail subsystems.     

PMaude: Rewrite-based Specification Language for Probabilistic Object Systems

We introduce a rewrite-based specification language for modelling probabilistic concurrent and distributed systems. The language, based on PMaude, has both a rigorous formal basis and the characteristics of a high-level rule-based programming language. Furthermore, we provide tool support for performing discrete-event simulations of models written in PMaude, and for statistically analyzing various quantitative aspects of such models based on the samples that are generated through discrete-event simulation. Because distributed and concurrent communication protocols can be modelled using actors (concurrent objects with asynchronous message passing), we provide an actor PMaude module. The module aids writing specifications in a probabilistic actor formalism. This allows us to easily write specifications that are purely probabilistic – and not just non-deterministic. The absence of such (un-quantified) non-determinism in a probabilistic system is necessary for a form of statistical analysis that we also discuss. Specifically, we introduce a query language called Quantitative Temporal Expressions (or QuaTEx in short), to query various quantitative aspects of a probabilistic model. We also describe a statistical technique to evaluate QuaTEx expressions for a probabilistic model.     

A timed semantics of Orc

Orc is a kernel language for structured concurrent programming. Orc provides three powerful combinators that define the structure of a concurrent computation. These combinators support sequential and concurrent execution, and concurrent execution with blocking and termination.Orc is particularly well-suited for task orchestration, a form of concurrent programming with applications in workflow, business process management, and web service orchestration. Orc provides constructs to orchestrate the concurrent invocation of services while managing time-outs, priorities, and failures of services or communication.Our previous work on the semantics of Orc focused on its asynchronous behavior. The inclusion of time or the effect of delay on a computation had not been modeled. In this paper, we define an operational semantics of Orc that allows reasoning about delays, which are introduced explicitly by time-based constructs or implicitly by network delays. We develop a number of identities among Orc expressions and define an equality relation that is a congruence. We also present a denotational semantics in which the meaning of an Orc program is a set of traces, and show that the two semantics are equivalent.     

A multiagent framework for coordinated parallel problem solving

Today’s organizations, under increasing pressure on the effectiveness and the increasing need for dealing with complex tasks beyond a single individual’s capabilities, need technological support in managing complex tasks that involve highly distributed and heterogeneous information sources and several actors. This paper describes CoPSF, a multiagent system middle-ware that simplifies the development of coordinated problem solving applications while ensuring standard compliance through a set of system services and agents. CoPSF hosts and serves multiple concurrent teams of problem solving contributing both to the limitation of communication overheads and to the reduction of redundant work across teams and organizations. The framework employs (i) an interleaved task decomposition and allocation approach, (ii) a mechanism for coordination of agents’ work, and (iii) a mechanism that enables synergy between parallel teams.     

Types for the Ambient Calculus

The ambient calculus is a concurrent calculus where the unifying notion of ambient is used to model many different constructs for distributed and mobile computation. We study a type system that describes several properties of ambient behavior. The type system allows ambients to be partitioned in disjoint sets (groups), according to the intended design of a system, in order to specify both the communication and the mobility behavior of ambients.     

A Computational Economy for IN Load Control Using a Multi-Agent System

Intelligent Networks (IN) are used in telecommunication networks to provide services that require a decision-making network element. The Service Control Point (SCP) can be overloaded when the number of service requests exceeds the SCPs designed capacity. Traditional IN load control algorithms assume a single service network model or use a centralized controller to find a solution. In this paper we propose and investigate a market-based model, in the form of a computational economy, for solving the distributed IN load control problem for a multi-service network. We investigate two algorithms, one price-oriented and the other resource-oriented, for finding the competitive equilibrium for this economy. We conclude that the price-oriented approach generally performs better and allows a greater level of distributed-decision making but suffers from an infeasible solution in real-time systems. Furthermore, we study a realization of this model as a multi-agent system (MAS) and investigate the communication overhead associated with running auctions for services.     

Software Model Checking: The VeriSoft Approach

Verification by state-space exploration, also often referred to as model checking, is an effective method for analyzing the correctness of concurrent reactive systems (for instance, communication protocols). Unfortunately, traditional model checking is restricted to the verification of properties of models, i.e., abstractions, of concurrent systems.We discuss in this paper how model checking can be extended to analyze arbitrary software, such as implementations of communication protocols written in programming languages like C or C++. We then introduce a search technique that is suitable for exploring the state spaces of such systems. This algorithm has been implemented in VeriSoft, a tool for systematically exploring the state spaces of systems composed of several concurrent processes executing arbitrary code.During the past five years, VeriSoft has been applied successfully for analyzing several software products developed in Lucent Technologies, and has also been licensed to hundreds of users in industry and academia. We discuss applications, strengths and limitations of VeriSoft, and compare it to other approaches to software model checking, analysis and testing.     

Message delay and DisCSP search algorithms

Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed search algorithms on DisCSPs. This has been recently shown in experimental studies of asynchronous backtracking algorithms (Bejar et al., Artif. Intell., 161:117–148, 2005; Silaghi and Faltings, Artif. Intell., 161:25–54, 2005). To evaluate the impact of message delay on the run of DisCSP search algorithms, a model for distributed performance measures is presented. The model counts the number of non concurrent constraints checks, to arrive at a solution, as a non concurrent measure of distributed computation. A simpler version measures distributed computation cost by the non-concurrent number of steps of computation. An algorithm for computing these distributed measures of computational effort is described. The realization of the model for measuring performance of distributed search algorithms is a simulator which includes the cost of message delays. Two families of distributed search algorithms on DisCSPs are investigated. Algorithms that run a single search process, and multiple search processes algorithms. The two families of algorithms are described and associated with existing algorithms. The performance of three representative algorithms of these two families is measured on randomly generated instances of DisCSPs with delayed messages. The delay of messages is found to have a strong negative effect on single search process algorithms, whether synchronous or asynchronous. Multi search process algorithms, on the other hand, are affected very lightly by message delay.     

A Simulation Study on Distributed Mutual Exclusion

In the problem of mutual exclusion, concurrent access to a shared resource using a structural program abstraction called acritical section(CS) must be synchronized such that at any time only one process can enter the CS. In a distributed system, due to the lack of both a shared memory and a global clock, and due to unpredictable message delay, the design of a distributed mutual exclusion algorithm that is free from deadlock and starvation is much more complex than that in a centralized system. Based on different assumptions about communication topologies and a widely varying amount of information maintained by each site about other sites, several distributed mutual exclusion algorithms have been proposed. In this paper, we suvrey and analyze several well-known distributed mutual exclusion algorithms according to their related characteristics. We also compare the performance of these algorithms by a simulation study. Finally, we present a comparative analysis of these algorithms.     

Join-Idle-Queue: A novel load balancing algorithm for dynamically scalable web services

The prevalence of dynamic-content web services, exemplified by search and online social networking, has motivated an increasingly wide web-facing front end. Horizontal scaling in the Cloud is favored for its elasticity, and distributed design of load balancers is highly desirable. Existing algorithms with a centralized design, such as Join-the-Shortest-Queue (JSQ), incur high communication overhead for distributed dispatchers.We propose a novel class of algorithms called Join-Idle-Queue (JIQ) for distributed load balancing in large systems. Unlike algorithms such as Power-of-Two, the JIQ algorithm incurs no communication overhead between the dispatchers and processors at job arrivals. We analyze the JIQ algorithm in the large system limit and find that it effectively results in a reduced system load, which produces 30-fold reduction in queueing overhead compared to Power-of-Two at medium to high load. An extension of the basic JIQ algorithm deals with very high loads using only local information of server load.     

The Esperanto Broker: a communication platform for nomadic computing systems

There is an increasing demand for middleware for nomadic computing applications. Owing to the inherent characteristics of such environments, these platforms have to address two fundamental issues: (i) device disconnections and the limitations of wireless networks may force users to experience short periods of service unavailability; and (ii) the complexity to design and develop next‐generation mobile computing applications. This paper proposes the Esperanto Broker (EB), a communication platform that addresses mobility issues via an integrated approach, i.e. at data‐link, network, and middleware levels. Decoupling interactions are achieved via a tuple‐space underlying infrastructure. To support developers with advanced services, the EB enhances the distributed objects computing model providing the abstraction for the communication paradigms standardized by the W3C. Esperanto applications can be modeled as sets of objects that are distributed over mobile devices, which communicate via remote method invocations (RMIs). RMIs natively implement pull and push models, in both one‐to‐one and one‐to‐many multiplicity. The paper focuses on the EB design issues, essential aspects of the implementation, and performance evaluations of the implemented prototype. Copyright © 2006 John Wiley & Sons, Ltd.     

Efficient monitoring of skyline queries over distributed data streams

Data management and data mining over distributed data streams have received considerable attention within the database community recently. This paper is the first work to address skyline queries over distributed data streams, where streams derive from multiple horizontally split data sources. Skyline query returns a set of interesting objects which are not dominated by any other objects within the base dataset. Previous work is concentrated on skyline computations over static data or centralized data streams. We present an efficient and an effective algorithm called BOCS to handle this issue under a more challenging environment of distributed streams. BOCS consists of an efficient centralized algorithm GridSky and an associated communication protocol. Based on the strategy of progressive refinement in BOCS, the skyline is incrementally computed by two phases. In the first phase, local skylines on remote sites are maintained by GridSky. At each time, only skyline increments on remote sites are sent to the coordinator. In the second phase, a global skyline is obtained by integrating remote increments with the latest global skyline. A theoretical analysis shows that BOCS is communication-optimal among all algorithms which use a share-nothing strategy. Extensive experiments demonstrate that our proposals are efficient, scalable, and stable.     

Utility servers in charlotte

Most distributed operating systems are built with a kernel replicated in each machine that supports only basic interprocess communication (IPC) and process control. All other system services, such as memory management, file system, and name service, are distributed in a set of utility servers, which are ordinary processes (except perhaps for some privileges) residing at various machines. Design and implementation of such utility servers in distributed environments are far different from those in a centralized system. This paper presents our experience in building utility servers in Charlotte, a message-based distributed operating system running on a loosely-coupled multicomputer. Utility services in Charlotte are provided by server squads. Each member in a squad covers services to its own community. The squad as a whole co-operatively provides services to the entire system. These servers are designed with the goals of simplicity, efficiency and robustness. They are intended to support a multiprogramming system for the development of distributed algorithms and other distributed applications. We address several major issues in developing a utility server, including the server structure, the management of message buffers, deadlock, and the robustness of server processes. Several utility servers in the Charlotte system are discussed as real examples.     

Distributed dynamic programming using concurrent object-orientedness with actors visualized by high-level Petri nets

This paper deals with application of concurrent object-oriented programming with Actors to solve dynamic programming problems in a distributed computing environment. This area of research is often called distributed artificial intelligence. Using a dynamic programming example of chained matrix multiplication, a method of managing dynamic programming searches in a distributed programming environment with Actors is presented. Distributed computations with Actors are visualized by means of Time-Varying Automata (for cases with no intra-actor concurrency) or using a class of high-level nets called Hierarchical Colored Petri Nets (for cases with intra-actor concurrency). Design and implementation features of the specific Actor-based programming environment, using a concurrent extension of C++, are also discussed.     

Decomposable algorithm for computing k-nearest neighbours across partitioned data

A common constraint in distributed data is that the database cannot be moved to other network sites due to computational costs, data size, or privacy considerations. All of the existing distributed algorithms for computing k-nearest neighbours (k-NNs) are designed for horizontally partitioned or special case of vertically partitioned data where different sites contain different attributes for a common set of entities. In this article, we present a framework including a general model and a decomposable algorithm for computing k-NN in d-dimensional space across horizontally and vertically partitioned data in the most general situation in which existing distributed databases want to cooperate for k-NN. The key is to obtain valid results, with a minimum information disclosure. The proposed algorithm preserves the privacy of the data at individual sites by requiring transmission of only minimal information to other sites. The computation is performed by exchanging minimum number of higher level summaries so that even if they are captured by an intruder to actual data tuples can ever be revealed.     

On the complexity of distributed stable matching with small messages

We consider the distributed complexity of the stable matching problem (a.k.a. “stable marriage”). In this problem, the communication graph is undirected and bipartite, and each node ranks its neighbors. Given a matching of the nodes, a pair of unmatched nodes is called blocking if they prefer each other to their assigned match. A matching is called stable if it does not induce any blocking pair. In the distributed model, nodes exchange messages in each round over the communication links, until they find a stable matching. We show that if messages may contain at most B bits each, then any distributed algorithm that solves the stable matching problem requires ${\Omega(\sqrt{n/B\log n})}We consider the distributed complexity of the stable matching problem (a.k.a. “stable marriage”). In this problem, the communication graph is undirected and bipartite, and each node ranks its neighbors. Given a matching of the nodes, a pair of unmatched nodes is called blocking if they prefer each other to their assigned match. A matching is called stable if it does not induce any blocking pair. In the distributed model, nodes exchange messages in each round over the communication links, until they find a stable matching. We show that if messages may contain at most B bits each, then any distributed algorithm that solves the stable matching problem requires W(?{n/Blogn}){\Omega(\sqrt{n/B\log n})} communication rounds in the worst case, even for graphs of diameter O(log n), where n is the number of nodes in the graph. Furthermore, the lower bound holds even if we allow the output to contain O(?n){O(\sqrt n)} blocking pairs, and if a pair is considered blocking only if they like each other much more then their assigned match.     

An Incremental Distributed Algorithm for Computing Biconnected Components in Dynamic Graphs

This paper describes a distributed algorithm for computing the biconnected components of a dynamically changing graph. Our algorithm has a worst-case communication complexity of O(b+c) messages for an edge insertion and O(b'+c) messages for an edge removal, and a worst-case time complexity of O(c) for both operations, where c is the maximum number of biconnected components in any of the connected components during the operation, b is the number of nodes in the biconnected component containing the new edge, and b' is the number of nodes in the biconnected component just before the deletion. The algorithm is presented in two stages. First, a serial algorithm is presented in which topology updates occur one at a time. Then, building on the serial algorithm, an algorithm is presented in which concurrent update requests are serialized within each connected component. The problem is motivated by the need to implement causal ordering of messages efficiently in a dynamically changing communication structure. Received January 1995; revised February 1997.     

Mapping MMOFPS over heterogeneous distributed systems

This paper evaluates the effects on performance of taking the heterogeneity of nodes into account, in terms of number of cores, when MMOFPS (Massively Multiplayer Online First Person Shooter) game services are distributed. Two mapping strategies, Non_Heterogeneity_aware and Heterogeneity_aware, are integrated in a system, called OnDeGaS (On Demand Game Service), which is a hybrid between Client-Server and P2P topologies. Through simulation, we show that the Heterogeneity_aware mechanism has more impact in communication costs, but it is more efficient in exploiting the nodes of the P2P area, as it maps players faster and it creates less computing zones with latency values under the acceptable threshold for MMOFPS games.     

Distributed stream join query processing with semijoins

This paper addresses the distributed stream processing of window-based multi-way join queries considering the semijoin as a key join operator. In distributed stream processing, data streams arriving at remote sites need to be shipped to the processing site for query execution. This typically introduces high communication overhead. Our observation is that semijoin, effective in reducing communication overhead in distributed database query processing, can be also effective in distributed stream query processing. The challenge, however, lies in the streaming nature of the tuples, as it requires continuous and incremental processing of an unbounded sequence of tuples instead of one-time processing of a set of stored tuples. This paper describes our comprehensive work done to address the challenge. Specifically, we first propose a distributed stream join processing model that handles the issue of network delays introduced from the shipment of data streams, and allows for efficient batch processing. Then, based on the model, we propose join algorithms in a multi-way join case: first, one-way join algorithms for different combinations of join placement and join method and, then, multi-way join algorithms assuming linear join ordering. Regarding the join method, two distributed join methods are introduced: (1) simple join, in which full tuples are forwarded to the query processing site and (2) semijoin-based join, in which partial tuples are forwarded. A semijoin-based join can be executed with different possible semijoin strategies which incur different communication overheads. We present a complete set of join algorithms considering all possible semijoin strategies, and propose an optimization algorithm. The join algorithms are executed continuously in an incremental manner as tuples arrive, and never ship tuples redundantly. The optimization algorithm constructs an efficient multi-way join plan by using a greedy heuristic which adds to the plan one stream with the minimum join execution cost in each step. Through extensive experiments, we conduct comparative studies of the performance among the proposed one-way join algorithms and the efficiency of the generated plan between the optimization algorithm based on the greedy heuristic and the exhaustive search, respectively.