Supporting disconnection operations through cooperative hoarding

Mobile clients often need to operate while disconnected from the network due to limited battery life and network coverage. Hoarding supports this by fetching frequently accessed data into clients' local caches prior to disconnection. Existing work on hoarding have focused on improving data accessibility for individual mobile clients. However, due to storage limitations, mobile clients may not be able to hoard every data object they need. This leads to cache misses and disruption to clients' operations. In this paper, a new concept called cooperative hoarding is introduced to reduce the risks of cache misses for mobile clients. Cooperative hoarding takes advantage of group mobility behaviour, combined with peer cooperation in ad-hoc mode, to improve hoard performance. Two cooperative hoarding approaches are proposed that take into account access frequency, connection probability, and cache size of mobile clients so that hoarding can be performed cooperatively. Simulation results show that the proposed methods significantly improve cache hit ratio and provides better support for disconnected operations compared to existing schemes

User-activity aware strategies for mobile information access

Information access suffers tremendously in wireless networks because of the low correlation between content transferred across low-bandwidth wireless links and actual data used to serve user requests. As a result, conventional content access mechanisms face such problems as unnecessary bandwidth consumption and large response times, and users experience significant performance degradation. In this dissertation, we analyze the cause of those problems and find that the major reason for inefficient information access in wireless networks is the absence of any user-activity awareness in current mechanisms. To solve these problems, we propose three user-activity aware strategies for mobile information access. Through simulations and implementations, we show that our strategies can outperform conventional information access schemes in terms of bandwidth consumption and user-perceived response times.Ph.D.Committee Chair: Raghupathy Sivakumar; Committee Member: Chuanyi Ji; Committee Member: George Riley; Committee Member: Magnus Egerstedt; Committee Member: Umakishore Ramachandra

Supporting disconnected operations in mobile computing

Mobile computing has enabled users to seamlessly access databases even when they are on the move. However, in the absence of readily available high-quality communication, users are often forced to operate disconnected from the network. As a result, software applications have to be redesigned to take advantage of this environment while accommodating the new challenges posed by mobility. In particular, there is a need for replication and synchronization services in order to guarantee availability of data and functionality, (including updates) in disconnected mode. To this end we propose a scalable and highly available data replication and management service. The proposed replication technique is compared with a baseline replication technique and shown to exhibit high availability, fault tolerance and minimal access times of the data and services, which are very important in an environment with low-quality communication links.<br /

Contention management for distributed data replication

PhD ThesisOptimistic replication schemes provide distributed applications with access to shared data at lower latencies and greater availability. This is achieved by allowing clients to replicate shared data and execute actions locally. A consequence of this scheme raises issues regarding shared data consistency. Sometimes an action executed by a client may result in shared data that may conflict and, as a consequence, may conflict with subsequent actions that are caused by the conflicting action. This requires a client to rollback to the action that caused the conflicting data, and to execute some exception handling. This can be achieved by relying on the application layer to either ignore or handle shared data inconsistencies when they are discovered during the reconciliation phase of an optimistic protocol. Inconsistency of shared data has an impact on the causality relationship across client actions. In protocol design, it is desirable to preserve the property of causality between different actions occurring across a distributed application. Without application level knowledge, we assume an action causes all the subsequent actions at the same client. With application knowledge, we can significantly ease the protocol burden of provisioning causal ordering, as we can identify which actions do not cause other actions (even if they precede them). This, in turn, makes possible the client’s ability to rollback to past actions and to change them, without having to alter subsequent actions. Unfortunately, increased instances of application level causal relations between actions lead to a significant overhead in protocol. Therefore, minimizing the rollback associated with conflicting actions, while preserving causality, is seen as desirable for lower exception handling in the application layer. In this thesis, we present a framework that utilizes causality to create a scheduler that can inform a contention management scheme to reduce the rollback associated with the conflicting access of shared data. Our framework uses a backoff contention management scheme to provide causality preserving for those optimistic replication systems with high causality requirements, without the need for application layer knowledge. We present experiments which demonstrate that our framework reduces clients’ rollback and, more importantly, that the overall throughput of the system is improved when the contention management is used with applications that require causality to be preserved across all actions

Scalable Proxy Architecture for Mobile and Peer-to-Peer Networks

The growth of wireless telecommunications has stipulated the interest for anywhere-anytime computing. The synergy between networking and mobility will engender new collaborative applications with mobile devices on heterogeneous platforms. One such middleware is “SYSTEM ON MOBILE DEVICES”, SYD developed by the Yamacraw Embedded Systems research team. This type of middleware is an opening step towards Peer-to-Peer mobile networks. This project envisioned collaborative applications among mobile devices and PDAs were used as servers. This thesis studies various existing architectures in mobile computing and their scalability issues. We also proposed new scalable flexible thick client proxy system FTCPS, an architecture suitable for mobile Peer-to-Peer networks. Our empirical study showed that FTCPS has low response time compared to other architectures

Association rules for supporting hoarding in mobile computing environments

One of the features that a mobile computer should provide is disconnected operation which is performed by hoarding. The process of hoarding can be described as loading the data items needed in the future to the client cache prior to disconnection. Automated hoarding is the process of predicting the hoard set without any user intervention. In this paper, we describe an application independent and generic technique for determining what should be hoarded prior to disconnection. Our method utilizes association rules that are extracted by data mining techniques for determining the set of items that should be hoarded to a mobile computer prior to disconnection. The proposed method was implemented and tested on synthetic data to estimate its effectiveness. Performance experiments determined that the proposed rule-based methods are effective in improving the system performance in terms of the cache hit ratio of mobile clients especially for small cache sizes

Location-aware computing: a neural network model for determining location in wireless LANs

The strengths of the RF signals arriving from more access points in a wireless LANs are related to the position of the mobile terminal and can be used to derive the location of the user. In a heterogeneous environment, e.g. inside a building or in a variegated urban geometry, the received power is a very complex function of the distance, the geometry, the materials. The complexity of the inverse problem (to derive the position from the signals) and the lack of complete information, motivate to consider flexible models based on a network of functions (neural networks). Specifying the value of the free parameters of the model requires a supervised learning strategy that starts from a set of labeled examples to construct a model that will then generalize in an appropriate manner when confronted with new data, not present in the training set. The advantage of the method is that it does not require ad-hoc infrastructure in addition to the wireless LAN, while the flexible modeling and learning capabilities of neural networks achieve lower errors in determining the position, are amenable to incremental improvements, and do not require the detailed knowledge of the access point locations and of the building characteristics. A user needs only a map of the working space and a small number of identified locations to train a system, as evidenced by the experimental results presented

Enlightening the Repercussion of Dark Data Management towards Malaysian SMEs Sustainability

The sheer volume of dark data impacts the costs for searching and producing appropriate information and imposes a wasted storage cost in operating budgets. Therefore, a grounded theory research was conducted to investigate the dark data phenomenon towards SMEs in Malaysia. Straussian Grounded Theory Methodology was deployed to analyze collected qualitative data to investigate the repercussions of dark data management towards sustainability of Small &amp; Medium enterprises in Malaysia. Consequently, the study found that dark data is a precious asset to leverage and maintain sustainable business, and a model on the repercussions of dark data management was proposed. Keywords: Dark Data Management; Malaysian SMEs; Dark Data Repercussion Model; Business Sustainability. eISSN: 2398-4287 © 2023. The Authors. Published for AMER and cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers. DOI:  https://doi.org/10.21834/e-bpj.v8iSI15.507

Context-aware hoarding of multimedia content in a largescale tour guide scenario: a case study on scaling issues of a multimedia tour guide

Abstract: This paper discusses scaling issues of a mobile multimedia tour guide. Making tourist-information available in a substantially large geographical area (e.g. a federal state in Austria) raises new questions, compared to providing similar information in a limited area (such as a museum). First, we have to assume a heterogeneous network infrastructure containing high and low bandwidth links and even total network loss. Video streaming is therefore not possible at any place. Secondly, the total amount of data grows linearly to the number of Points of Interest (POIs) which are augmented by the tour guide. Therefore, a preloading of all data onto a device with limited storage is not possible. A possible solution to these problems is hoarding, i.e. preloading an &quot;appropriate&quot; subset of data. The crucial question is to find the proper subset in dependence of the actual context. The paper discusses the questions o