An increasingly common application for DLTs is their exploitation in enterprise systems operated by a consortium of organizations, who may assume different roles and whose interaction takes place over a blockchain network (in this scope, often permissioned), which holds a data state that they need to query frequently. In this regard, one of the main drawbacks of DLTs is their unsuitability for the efficient execution of complex queries on the data stored by the nodes comprising the network. Arising from this issue, many solutions propose to dump the ledger contents into databases, which, due to their own nature and purpose, are certainly optimized for the execution of such queries. However, most proposals on this area are not intended for querying the shared state held by the network, just the transaction history. Actually, through conducting a study on the state of the art, a lack of support for handling and querying complex structured data has been identified. DELTA provides a solution for the synchronization, with negligible overload, of the state of a DLT into a database, enabling (a) the operation with smart contracts whose data possess a complex structure and (b) the efficient execution of elaborate queries on these data. By using DELTA, query times decrease, at least, between one and five orders of magnitude, depending on the DLT, compared to queries directed to the ledger nodes.

The CAP theorem states that only two of these properties can be simultaneously guaranteed in a distributed service: (i) consistency, (ii) availability and (iii) network partition tolerance. This theorem was stated and proved assuming that ‘consistency’ refers to atomic consistency. However, multiple consistency models exist and atomic consistency is located at the strongest edge of that spectrum. Many distributed services deployed in cloud platforms should be highly available and scalable. Network partitions may arise in those deployments and should be tolerated. One way of dealing with CAP constraints consists in relaxing consistency. Therefore, it is interesting to explore the set of consistency models not supported in an available and partition-tolerant service (CAP-constrained models). Other weaker consistency models could be maintained when scalable services are deployed in partitionable systems (CAP-free models). Three contributions arise: (i) multiple other CAP-constrained models are identified, (ii) a borderline between CAP-constrained and CAP-free models is set and (iii) a hierarchy of consistency models depending on their strength and convergence is built.

Current multicomputerdesigns based on the k -ary d-cube topology present two main drawbacks when used as general purpose computers: They couple processing and communication capacities, and, when the dimension is kept fixed, the bisection bandwidth availability for each node decreases as the number of processing nodes grows.To overcome the above shortcomings, it is possible to apply a strategy we refer to as overrouting to k-ary d-cube networks.Two interconnection schemes resulting from such strategy are the k-ary d-cube n-spaces networks and the k-ary d-cube z-overrouted networks.The present paper compares the relative merits and demerits of those two schemes.

In this work a new distributed deadlock resolution algorithm for the OR model is proposed. The algorithm verifies the correctness criteria: safety-false deadlocks are not resolved; and liveness-deadlocks are resolved in finite time.

Previous proposals for Distributed Deadlock Detection/Resolution algorithms for the AND model have the main disadvantage of resolving false deadlocks, that is, nonexisting or currently being resolved deadlocks. This paper provides an algorithm free of false deadlock resolutions, A simple specification for a safe deadlock resolution algorithm is introduced, and the new distributed solution is developed in a hierarchical fashion from its abstract specification. The algorithm is probe-based, uses node priorities, and coordinates the actions of resolvers so that false deadlocks are not resolved. The solution is formally proven correct by using the input-output Automata Model. Finally, a study about the liveness of the algorithm is provided.

Distributed shared memory (DSM) is a paradigm for programming distributed systems, which provides an alternative to the message passing model. DSM offers the agents of the system a shared address space through which they can communicate with each other. The main problem of a DSM implementation on top of a message passing system is performance. Performance of an implementation is closely related to the consistency the DSM system offers: strong consistency (all agents agree about how memory events happen) and is more expensive to implement than weak consistency (disagreements are allowed). There have been many DSM systems proposals, each one supporting different consistency levels. Experience has shown that no one is well suited for the whole range of problems. In some cases, strong consistent primitives are not needed, while in other cases, the weak semantics provided are useless. This is also true for different implementations of the same memory model, since performance is also affected by the data access patterns of the applications. We introduce a novel DSM model called Mume. Mume is a low level layer close to the level of the message passing interface. The Mume interface provides only the minimum requirements to be considered as a shared memory system. The interface includes three types of synchronization primitives, namely total ordering, causal ordering and mutual exclusion. This allows efficient implementations of different memory access semantics, accommodating particular data access patterns.

The reliable object invocation mechanism provided by HIDRA for the coordinator-cohort and the passive replication models offers support to ensure that all the replicas of the object being invoked are correctly updated before such an invocation is terminated. This mechanism also ensures that if a primary or coordinator replica crashes, the client is able to reconnect to the previously initiated invocations, collecting their results without requiring their reexecution. All this support is provided transparently to the client of the replicated objects, which does not notice any difference in respect to the invocations made to non-replicated objects. Moreover, the protocols described in the paper deal also with the failure of any of the objects involved in this kind of invocations.

The process of searching for a resource in a distributed system whose nodes are connected through a store-and-forward network is modeled. Based on this model, a lower bound on the number of messages needed for finding a resource when nothing is known about its location is shown. The model also helps to establish some results about the complexity of finding optimal algorithms to locate a resource when the probability distribution for the location of the resource is known. It is shown that the optimization problem is NP-hard for general networks. An algorithm is developed for tree networks which can be specialized to polynomial algorithms for a class of trees. (The polynomial algorithms can be used as the basis of heuristic algorithms for general networks.) An application of this algorithm for path networks can be adapted to find optimal search algorithms for bidirectional ring networks.>

A protocol is presented to locate (or find) named resources in a distributed system which uses the multicast capabilities of the underlying network. Each node in the network uses a sequence of node groups, and each node group is associated with a unique multicast address. To locate a resource, the searching node sequentially polls each one of the groups until the resource is found; this scheme is a generalization of both pure polling and broadcast. To obtain an optimal division of the nodes into multicast groups, the protocol is analyzed and an efficient algorithm is given that provides a group division minimizing the expected cost per location operation.>

The authors address the problem of determining how system parameters affect the performance of the location operations when hint tables are used. To this end they approximate a distributed system incorporating hint tables in its location strategy with an analytic model. They identify a set of parameters affecting the cost of location operations and provide a criterion to help decide whether the use of hint tables should be incorporated in the design of a given system. They give a set of examples to illustrate the usage of the analytic results. These include location using: broadcast in a broadcast network; name servers in a broadcast network; broadcast is a packet switched network and name servers in a packet switched network.>

The authors present a resource (e.g. file, process) location scheme which utilizes the multicast communication capability of local area networks (LANs). In the scheme, the universe of resource names is partitioned into a relatively small number of groups and each group is assigned a unique address. Nodes storing the locations of resources belonging to a particular group instruct their network interfaces to receive all location messages sent to the group address. To locate a resource, a node first determines the address of the group to which the resource belongs, and a multicast message is then sent to the address. The algorithm performance is studied by simulation, and approximate closed-form solutions are derived for systems operating at heavy and low loads. The scheme's performance is compared with that of broadcast, and it is shown that the proposed scheme performs much better than broadcast alone.>