Software DSM protocols that adapt between single writer and multiple writer

We present two software DSM protocols that dynamically adapt between a single writer (SW) and a multiple writer (MW) protocol based on the application's sharing patterns. The first protocol (WFS) adapts based on write-write false sharing; the second (WFS+WG) based on a combination of write-write false sharing and write granularity. The adaptation is automatic. No user or compiler information is needed. The choice between SW and MW is made on a per-page basis. We measured the performance of our adaptive protocols on an 8-node SPARC cluster connected by a 155 Mbps ATM network. We used eight applications, covering a broad spectrum in terms of write-write false sharing and write granularity. We compare our adaptive protocols against the MW-only and the SW-only approach. Adaptation to write-write false sharing proves to be the critical performance factor, while adaptation to write granularity plays only a secondary role in our environment and for the applications considered. Each of the two adaptive protocols matches or exceeds the performance of the best of MW and SW in seven out of the eight application

Modular and generic IoT management on the cloud

Cloud computing and Internet of Things encompass various physical devices that generate and exchange data with services promoting the integration between the physical world and computer-based systems. This work presents a novel Future Internet cloud service for data collection from Internet of Things devices in an automatic, generalized and modular way. It includes a flexible API for managing devices, users and permissions by mapping data to users, publish and subscribe context data as well as storage capabilities and data processing in the form of NoSQL big data. The contributions of this work include the on the fly data collection from devices that is stored in cloud scalable databases, the vendor agnostic Internet of Things device connectivity (since it is designed to be flexible and to support device heterogeneity), and finally the modularity of the event based publish/subscribe service for context oriented data that could be easily utilized by third party services without worrying about how data are collected, stored and managed

Virtual machine cluster mobility in inter-cloud platforms

Modern cloud computing applications developed from different interoperable services that are interfacing with each other in a loose coupling approach. This work proposes the concept of the Virtual Machine (VM) cluster migration, meaning that services could be migrated to various clouds based on different constraints such as computational resources and better economical offerings. Since cloud services are instantiated as VMs, an application can be seen as a cluster of VMs that integrate its functionality. We focus on the VM cluster migration by exploring a more sophisticated method with regards to VM network configurations. In particular, networks are hard to managed because their internal setup is changed after a migration, and this is related with the configuration parameters during the re-instantiation to the new cloud platform. To address such issue, we introduce a Software Defined Networking (SDN) service that breaks the problem of network configuration into tractable pieces and involves virtual bridges instead of references to static endpoints. The architecture is modular, it is based on the SDN OpenFlow protocol and allows VMs to be paired in cluster groups that communicate with each other independently of the cloud platform that are deployed. The experimental analysis demonstrates migrations of VM clusters and provides a detailed discussion of service performance for different cases

Software distributed shared memory protocols that adapt between single writer and multiple writer

We present two software distributed shared memory protocols that dynamically adapt between a single writer (SW) and a multiple writer (MW) protocol based on the application's sharing patterns. The first protocol adapts based on write-write false sharing, the second based on a combination of write-write false sharing and write granularity. The adaptation is automatic. No user or compiler information is needed. We measured the performance of these protocols on a test suite of eight applications, covering a broad spectrum in terms of write-write false sharing and write granularity. The adaptive protocols match or exceed the performance of the best of MW and SW in seven out of the eight applications. Speedup improvements over SW range from a factor of 1.02 to 2.7, and over MW from 1.02 to 1.6. In addition, memory usage is reduced considerably compared to MW, in some cases making the memory overhead all but negligible

Conflict -aware replication for dynamic content Web sites

Conflict-aware replication is a novel lazy replication technique for scaling the back-end database of a dynamic content web server using a cluster of commodity computers. This technique provides both throughput scaling and 1-copy serializability. It has generally been believed that this combination is hard to achieve through replication because of the growth of the number of conflicts. Conflict-aware replication interposes a (possibly replicated) scheduler between the database and application server tiers. The conflict-aware scheduler directs incoming queries in such a way that the overall execution is serializable and the number of conflicts is reduced. The technique requires that the incoming transactions specify the tables that they access at the beginning of the transaction. Using this information, conflict-aware replication provides both scaling and 1-copy serializability, while it avoids making any changes to the application server or database. We have implemented a prototype of the conflict-aware scheduler in a cluster-based dynamic content site. We have also implemented various other scheduler algorithms in this prototype for comparison purposes, including conflict-aware and oblivious, with 1-copy serializability and with different looser consistency models. We have evaluated this method using the industry standard TPC-W e-commerce benchmark, an auction site benchmark, modeled after eBay.com, and a bulletin board benchmark, modeled after slashdot.org. For these applications, we have found that pre-specifying what tables are accessed involves very little work on behalf of the programmer and could easily be automated. For clusters with small number of database machines (up to 8) we have measured an implementation of the algorithms. We use simulation to extend our measurement results to larger clusters, faster database engines, and lower conflict rates. This dissertation shows that conflict-awareness brings considerable benefits in terms of both overall throughput scaling and latency reduction compared to both eager and conflict-oblivious lazy replication for a large range of cluster configurations and conflict rates. Furthermore, for all our applications, except those with very high conflict rates, the performance of conflict-aware replication equals or approaches that of looser consistency models. The dissertation also shows that the cost of conflict-aware replication is minimal in terms of data availability and fault tolerance