P. Bertok

Bio: P. Bertok is an academic researcher from Melbourne Institute of Technology. The author has contributed to research in topics: Cache & Cache pollution. The author has an hindex of 3, co-authored 4 publications receiving 70 citations.

Location-aware cache replacement for mobile environments

Abstract: Traditional cache replacement policies rely on the temporal locality of users' access pattern to improve cache performance. These policies, however, are not ideal in supporting mobile clients. As mobile clients can move freely from one location to another, their access pattern not only exhibits temporal locality, but also exhibits spatial locality. In order to ensure efficient cache utilisation, it is important to take into consideration the location and movement direction of mobile clients when performing cache replacement. In this paper. we propose a mobility-aware cache replacement policy, called MARS, suitable for wireless environments. MARS takes into account important factors (e.g. client access rate, access probability, update probability and client location) in order to improve the effectiveness of onboard caching for mobile clients. Test results show that MARS consistently outperforms existing cache replacement policies and significantly improves mobile clients' cache hit ratio.

Mobility-aware cache replacement for users of location-dependent services

Abstract: Recent advances in wireless communication and global positioning technologies have led to increasing interest in location dependent information services. As mobile users move between locations utilising such services, their access patterns not only exhibit temporal locality, but also spatial locality. Traditional cache replacement policies were designed to deal with temporal locality, as a result, they are inefficient location dependent services. In this paper a mobility-aware algorithm called MARS+ is proposed to detect regular client movement patterns and provides information to improve cache performance. Test results show that MARS+ improves clients' cache hit ratio by more than 16% compared to existing policies.

A mobile cache consistency protocol using shareable read/write time locks

Abstract: Object caching is often used to improve the performance of mobile applications, but the gain is often lessened by the additional load of maintaining consistency between an original object and its cached copy. This paper aims at reducing the consistency maintenance work and proposes a protocol that distinguishes between two classes of consistency (i.e. weak and strong) and treats them differently. Strong consistency is used for data that needs to be consistent all the time, whereas weak consistency is for cases when stale data can be tolerated or only specific updates are relevant to the application. Consistency is maintained by using strict and permissive read/write time locks that enable data sharing for a fixed time period and support concurrency control. A notification protocol for propagating updates to clients is also proposed. Performance tests have shown that switching from strong to weak consistency reduces the number of aborts due to conflicting operations by almost half even with high read/write sharing.

Improving data accessibility for mobile clients through cooperative hoarding

Abstract: In this paper, we introduce the concept of cooperative hoarding 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 that take into account clients' access frequencies, connection probabilities and cache size when performing hoarding are proposed. Test results show that the proposed methods significantly improve cache hit ratio and reduce query costs compared to existing approaches.

Money as tool, money as drug: The biological psychology of a strong incentive

Abstract: Why are people interested in money? Specifically, what could be the biological basis for the extraordinary incentive and reinforcing power of money, which seems to be unique to the human species? We identify two ways in which a commodity which is of no biological significance in itself can become a strong motivator. The first is if it is used as a tool, and by a metaphorical extension this is often applied to money: it is used instrumentally, in order to obtain biologically relevant incentives. Second, substances can be strong motivators because they imitate the action of natural incentives but do not produce the fitness gains for which those incentives are instinctively sought. The classic examples of this process are psychoactive drugs, but we argue that the drug concept can also be extended metaphorically to provide an account of money motivation. From a review of theoretical and empirical literature about money, we conclude that (i) there are a number of phenomena that cannot be accounted for by a pure Tool Theory of money motivation; (ii) supplementing Tool Theory with a Drug Theory enables the anomalous phenomena to be explained; and (iii) the human instincts that, according to a Drug Theory, money parasitizes include trading (derived from reciprocal altruism) and object play.

Toward green media delivery: location-aware opportunities and approaches

Abstract: Mobile media has undoubtedly become the predominant source of traffic in wireless networks. The result is not only congestion and poor quality of experience, but also an unprecedented energy drain at both the network and user devices. In order to sustain this continued growth, novel disruptive paradigms of media delivery are urgently needed. We envision that two key contemporary advancements can be leveraged to develop greener media delivery platforms: The proliferation of navigation hardware and software in mobile devices has created an era of location awareness, where both the current and future user locations can be predicted; and the rise of context-aware network architectures and self-organizing functionalities is enabling context signaling and in-network adaptation. With these developments in mind, this article investigates the opportunities of exploiting location awareness to enable green end-to-end media delivery. In particular, we discuss and propose approaches for location-based adaptive video quality planning, in-network caching, content prefetching, and long-term radio resource management. To provide insights on the energy savings, we then present a cross-layer framework that jointly optimizes resource allocation and multi-user video quality using location predictions. Finally, we highlight some of the future research directions for location-aware media delivery in the conclusion.

A weighted cache replacement policy for location dependent data in mobile environments

Abstract: Developing widely useful mobile computing applications presents difficult challenges. On one hand, mobile users demand intuitive user interfaces, fast response times, and deep relevant content. On the other hand, mobile devices have limited processing, storage, power, display, and communication resources. Caching frequently accessed data items on the mobile client is an effective technique to improve the system performance in mobile environment. Due to cache size limitation, the choice of cache replacement technique to find a suitable subset of items for eviction from cache becomes important. In this paper, we propose a new cache replacement policy for location dependent data in mobile environment. The proposed policy selects the predicted region based on client's movement and uses it to calculate the weighted data distance of an item. This makes the policy adaptive to client's movement pattern and provides importance to the regions around client's position. This is unlike earlier policies that consider the directional/non-directional data distance only. We call our policy the Weighted Predicted Region based Cache Replacement Policy (WPRRP). Simulation results show that the proposed policy significantly improves the system performance in comparison to previous schemes in terms of cache hit ratio.

A Predicted Region based Cache Replacement Policy for Location Dependent Data in Mobile Environment

Abstract: Caching frequently accessed data items on the mobile client is an effective technique to improve the system performance in mobile environment. Proper choice of cache replacement technique to find a suitable subset of items for eviction from cache is very important because of limited cache size. Available policies do not take into account the movement patterns of the client. In this paper, we propose a new cache replacement policy for location dependent data in mobile environment. The proposed policy uses a predicted region based cost function to select an item for eviction from cache. The policy selects the predicted region based on client’s movement and uses it to calculate the data distance of an item. This makes the policy adaptive to client’s movement pattern unlike earlier policies that consider the directional / non-directional data distance only. We call our policy the Prioritized Predicted Region based Cache Replacement Policy (PPRRP). Simulation results show that the proposed policy significantly improves the system performance in comparison to previous schemes in terms of cache hit ratio.