Farhana Jabeen

Comprehensive Optimization of Declarative Sensor Network Queries

We present a sensor network query processing architecture that covers all the query optimization phases that are required to map a declarative query to executable code. The architecture is founded on the view that a sensor network truly is a distributed computing infrastructure, albeit a very constrained one. As such, we address the problem of how to develop a comprehensive optimizer for an expressive declarative continuous query language over acquisitional streams as one of finding extensions to classical distributed query processing techniques that contend with the peculiarities of sensor networks as an environment for distributed computing.

An Architecture for Query Optimization in Sensor Networks

We present a novel sensor network query processing architecture that (a) covers all the query optimization phases that are required to map a declarative query to executable code; and (b) does so for a more expressive query language than has heretofore been supported over sensor networks. The architecture is founded on the view that a sensor network truly is a distributed computing infrastructure, albeit a very constrained one. As such, we address the problem of how to develop a comprehensive optimizer for an expressive declarative continuous query language over acquisitional streams as one of finding extensions to a classical distributed query processing architecture that contend with the peculiarities of sensor networks as an environment for distributed computing.

In-network wireless sensor network query processors

Introducing the highly constrained distributed computing platform that sensor networks give rise to.Outline the challenges in conducting in-network query processing in WSN.Compared state-of-the-art SNQPs in terms of their query language, compiler support and kind of queries supported.Presented evaluation framework. Describe limitations of state-of-the-art SNQPs.Future research scopes of query processing in WSNs. In wireless sensor networks (WSNs), energy is valuable because it is scarce. This causes their life time to be determined by their ability to use the available energy in an effective and frugal manner. In most of the earlier sensor network applications, the main requirement consisted mainly of data collection but transmitting all of the raw data out of the network may be prohibitively expensive (in terms of communication) or impossible at given data collection rates.In the last decade, the use of the database paradigm has emerged as a feasible solution to manage data in a WSN context. There are various sensor network query processors (SNQPs) (implementing in-network declarative query processing) that provide data reduction, aggregation, logging, and auditing facilities. These SNQPs view the wireless sensor network as a distributed database over which declarative query processor can be used to program a WSN application with much less effort. They allow users to pose declarative queries that provide an effective and efficient means to obtain data about the physical environment, as users would not need to be concerned with how sensors are to acquire the data, or how nodes transform and/or transmit the data.This paper surveys novel approaches of handling query processing by the current SNQP literature, the expressiveness of their query language, the support provided by their compiler/optimizer to generate efficient query plans and the kind of queries supported. We introduce the challenges and opportunities of research in the field of in-network sensor network query processing as well as illustrate the current status of research and future research scopes in this field.

Trustworthy data: A survey, taxonomy and future trends of secure provenance schemes

Abstract Data is a valuable asset for the success of business and organizations these days, as it is effectively utilized for decision making, risk assessment, prioritizing the goals and performance evaluation. Extreme reliance on data demands quality assurance and trust on processes. Data Provenance is information that can be used to reason about the current state of a data object. Provenance can be broadly described as the information that explains where a piece of data object came from, how it was derived or created, who was involved in said creation, manipulations involved, processes applied, etc. It consists of information that had an effect on the data, evolving to its present state. Provenance has been used widely for the authenticity of data and processes. Despite having such a wide range of uses and applications, provenance poses vexing privacy and integrity challenges. Provenance data itself is, therefore, critical and it must be secured. Over the years, a number of secure provenance schemes have been proposed. This paper aims to enhance the understanding of secure provenance schemes and its associated security issues. In this paper, we have discussed why secure provenance is needed, what are its essential characteristics, and what objectives it serves? We describe the lifecycle of secure provenance and highlighted how trust is achieved in different domains by its application. Firstly, a detailed taxonomy of existing secure provenance schemes is presented. Then, a comparative analysis of existing secure provenance schemes, which highlights their strengths and weaknesses is also provided. Furthermore; we highlight future trends, which should be focused upon by the research community.

An algorithmic strategy for in-network distributed spatial analysis in wireless sensor networks

A wireless sensor network (WSN) can be construed as an intelligent, largely autonomous, instrument for scientific observation at fine temporal and spatial granularities and over large areas. The ability to perform spatial analyses over sensor data has often been highlighted as desirable in areas such as environmental monitoring. Whilst there exists research on computing topological changes of dynamic phenomena, existing proposals do not allow for more expressive in-network spatial analysis. This paper addresses the challenges involved in using WSNs to identify, track and report topological relationships between dynamic, transient spatial phenomena and permanent application-specific geometries focusing on cases where the geometries involved can be characterized by sets of nodes embedded in a finite 2-dimensional space. The approach taken is algebraic, i.e., analyses are expressed as algebraic expressions that compose primitive operations (such as Adjacent, or AreaInside). The main contributions are distributed algorithms for the operations in the proposed algebra and an empirical evaluation of their performance in terms of bit complexity, response time, and energy consumption.

Monitoring Spatially Referenced Entities in Wireless Sensor Networks

Wireless sensor networks (WSNs) make it possible to gather information about the physical world in novel ways and in unprecedented levels of detail. In the environmental sciences, in particular, WSNs are on the way to becoming an important tool for monitoring spatially- and temporally-extended physical phenomena. However, support for high-level and expressive spatio-analytic tasks to explore relationships between spatially referenced entities (e.g., whether mist is over a vineyard or has not yet touched it) and to derive representations grounded on such relationships (e.g., the geometrical extent of that part of a vineyard that is covered by mist) is still incipient, particularly in the case of in-network processing approaches that are imperative, due to energy scarcity, in mote-level WSNs. This paper describes distributed implementations of a comprehensive collection of spatio-algebraic operations that enable the expression and evaluation of tasks involving spatial predicates as well as the derivation of new geometries from existing geometries. This makes it possible to report back only fine-grained information.

Secure provenance using an authenticated data structure approach

Abstract Data provenance is information used in reasoning about the present state of a data object, providing details such as the inputs used, transformations it underwent, entities responsible, and any other information that had an impact on its evolution. With a plethora of uses consisting of but not limited to provision of trust, gauging of quality, detecting intrusion and system changes, solving attribution problems, regulations compliance and in legal proceedings etc., provenance information needs to be secured. On the other hand use of tampered provenance information could lead to erroneous judgments and serious implications in many situations. The difference in sensitivity levels of provenance and the underlying data coupled with its DAG (Directed Acyclic Graph) structure leads to the need for a tailored security model. To date, proposed secure provenance schemes such as the Onion scheme, PKLC scheme, Mutual agreement scheme, rely on transitive trust; consecutive participating entities do not collude to attack the provenance chain. Furthermore, these schemes suffer from attacks such as ownership and lone attacks on provenance records. We propose a secure provenance scheme that uses the auditor as a witness to the chain build process whereby a verification tree is incrementally built by the auditor which serves as his view of the chain. Our scheme removes the transitive trust dependency hence collusion attacks by consecutive participating entities are successfully detected. Additionally, our scheme captures the DAG structure of provenance information and achieves secure provenance requirements; integrity, availability and confidentiality. Security analysis and empirical results show that the scheme provides better security guarantees than the previously proposed schemes with reasonable overheads involved that can be outweighed by the protection capabilities provided and removal of transitive trust which may not be feasible.

Spatio-Temporal Query Processing Over Sensor Networks: Challenges, State Of The Art And Future Directions

Wireless sensor networks (WSNs) are likely to be more prevalent as their cost-effectiveness improves. The spectrum of applications for WSNs spans multiple domains. In environmental sciences, in particular, they are on the way to become an essential technology for monitoring the natural environment and the dynamic behavior of transient physical phenomena over space. Existing sensor network query processors (SNQPs) have also demonstrated that in-network processing is an effective and efficient means of interaction with WSNs for performing queries over live data. Inspired by these findings, this paper investigates the question as to whether spatio-temporal and historical analysis can be carried over WSNs using distributed query-processing techniques. The emphasis of this work is on the spatial, temporal and historical aspects of sensed data, which are not adequately addressed in existing SNQPs. This paper surveys the novel approaches of storing the data and execution of spatio-temporal and historical queries. We introduce the challenges and opportunities of research in the field of in-network storage and in-network spatio-temporal query processing as well as illustrate the current status of research in this field. We also present new areas where the spatio-temporal and historical query processing can be of significant importance.

Towards a set aggregation-based data integrity scheme for smart grids

Data aggregation (DA) is the process of combining smart metering data so that it can be sent to a control center in package form rather than as individual data points. Smart metering data represents sensitive information that must be protected during the aggregation process. Traditional data aggregation schemes have addressed privacy issues based primarily on computationally expensive homomorphic encryption. In contrast, this paper presents a novel method based on hash chaining to verify the integrity of a set of aggregated data. This scheme divides the user’s data into two diverse groups. It also enables the control center to collect more fine-grained data aggregation results at a reduced cost. In addition, the proposed scheme ensures data integrity by maintaining a hash chain and assigning new values in the hash chain by XORing previous hash values with the current hash value. The proposed scheme is evaluated in terms of computational cost and communication overhead. A comparative analysis of our proposed methodology with existing aggregation schemes regarding computational cost and communication overhead illustrates the optimality of our proposed scheme.

Analysis of Co-Channel Interference in VANETs under Nakagami-m Fading

Vehicular networks have become one of the most anticipated technologies of the current century due to their application oriented nature. This paper adopts the cluster based approach to analytically model the implications of interference in Vehicular Ad-hoc Networks (VANETs). To be specific, we derive a closed form expression for packet error probability for co-channel interference under Nakagami-m fading channel. Impact of Nakagami-m shape factor on interference is also characterized in detail. We then derive an expression for antenna selection scheme and obtain noteworthy enhancement in performance of cluster. Extensive simulations are performed to validate our findings which clearly prove the practical significance of our analytical model.