2 research outputs found
An Elastic Middleware Platform for Concurrent and Distributed Cloud and MapReduce Simulations
Cloud Computing researches involve a tremendous amount of entities such as
users, applications, and virtual machines. Due to the limited access and often
variable availability of such resources, researchers have their prototypes
tested against the simulation environments, opposed to the real cloud
environments. Existing cloud simulation environments such as CloudSim and
EmuSim are executed sequentially, where a more advanced cloud simulation tool
could be created extending them, leveraging the latest technologies as well as
the availability of multi-core computers and the clusters in the research
laboratories. While computing has been evolving with multi-core programming,
MapReduce paradigms, and middleware platforms, cloud and MapReduce simulations
still fail to exploit these developments themselves. This research develops
Cloud2Sim, which tries to fill the gap between the simulations and the actual
technology that they are trying to simulate.
First, Cloud2Sim provides a concurrent and distributed cloud simulator, by
extending CloudSim cloud simulator, using Hazelcast in-memory key-value store.
Then, it also provides a quick assessment to MapReduce implementations of
Hazelcast and Infinispan, adaptively distributing the execution to a cluster,
providing means of simulating MapReduce executions. The dynamic scaler solution
scales out the cloud and MapReduce simulations to multiple nodes running
Hazelcast and Infinispan, based on load. The distributed execution model and
adaptive scaling solution could be leveraged as a general purpose auto scaler
middleware for a multi-tenanted deployment.Comment: Thesis to obtain the Master of Science Degree in Information Systems
and Computer Engineering, Instituto Superior Tecnico, Universidade de Lisboa.
2014 Septembe
Incremental replication for mobility support in OBIWAN
The need for sharing is well known in a large number of distributed collaborative applications. These applications are difficult to develop for wide area (possibly mobile) networks because of slow and unreliable connections. For this purpose, we developed a platform called OBI-WAN 1 that: i) allows the application to decide, in run-time, the mechanism by which objects should be invoked, remote method invocation or invocation on a local replica, ii) allows incremental replication of large object graphs, iii) allows the creation of dynamic clusters of data, and iv) provides hooks for the application programmer to implement a set of application specific properties such as relaxed transactional support or updates dissemination. These mechanisms allow an application to deal with situations that frequently occur in a (mobile) wide-area network, such as disconnections and slow links: i) as long as objects needed by an application (or by an agent) are colocated, there is no need to be connected to the network, and ii) it is possible to replace, in run-time, remote by local invocations on replicas, thus improving the performance and adaptability of applications. The prototype is developed in Java, is very small and simple to use, the performance results are very encouraging, and existing applications can be easily modified to take advantage of OBIWAN.