Role of genetic and social factors in modulating the efficiency of division of labour in social insects

Summary : Division of labour is one of the most fascinating aspects of social insects. The efficient allocation of individuals to a multitude of different tasks requires a dynamic adjustment in response to the demands of a changing environment. A considerable number of theoretical models have focussed on identifying the mechanisms allowing colonies to perform efficient task allocation. The large majority of these models are built on the observation that individuals in a colony vary in their propensity (response threshold) to perform different tasks. Since individuals with a low threshold for a given task stimulus are more likely to perform that task than individuals with a high threshold, infra-colony variation in individual thresholds results in colony division of labour. These theoretical models suggest that variation in individual thresholds is affected by the within-colony genetic diversity. However, the models have not considered the genetic architecture underlying the individual response thresholds. This is important because a better understanding of division of labour requires determining how genotypic variation relates to differences in infra-colony response threshold distributions. In this thesis, we investigated the combined influence on task allocation efficiency of both, the within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes underlying the response thresholds. We used an agent-based simulator to model a situation where workers in a colony had to perform either a regulatory task (where the amount of a given food item in the colony had to be maintained within predefined bounds) or a foraging task (where the quantity of a second type of food item collected had to be the highest possible). The performance of colonies was a function of workers being able to perform both tasks efficiently. To study the effect of within-colony genetic diversity, we compared the performance of colonies with queens mated with varying number of males. On the other hand, the influence of genetic architecture was investigated by varying the number of loci underlying the response threshold of the foraging and regulatory tasks. Artificial evolution was used to evolve the allelic values underlying the tasks thresholds. The results revealed that multiple matings always translated into higher colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or few genes for the foraging task's threshold. By contrast, higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes determining the threshold for the regulatory task only had a minor but incremental effect on colony performance. Overall, our numerical experiments indicate the importance of considering the effects of queen mating frequency, genetic architecture underlying task thresholds and the type of task performed when investigating the factors regulating the efficiency of division of labour in social insects. In this thesis we also investigate the task allocation efficiency of response threshold models and compare them with neural networks. While response threshold models are widely used amongst theoretical biologists interested in division of labour in social insects, our simulation reveals that they perform poorly compared to a neural network model. A major shortcoming of response thresholds is that they fail at one of the most crucial requirement of division of labour, the ability of individuals in a colony to efficiently switch between tasks under varying environmental conditions. Moreover, the intrinsic properties of the threshold models are that they lead to a large proportion of idle workers. Our results highlight these limitations of the response threshold models and provide an adequate substitute. Altogether, the experiments presented in this thesis provide novel contributions to the understanding of how division of labour in social insects is influenced by queen mating frequency and genetic architecture underlying worker task thresholds. Moreover, the thesis also provides a novel model of the mechanisms underlying worker task allocation that maybe more generally applicable than the widely used response threshold models. Resumé : La répartition du travail est l'un des aspects les plus fascinants des insectes vivant en société. Une allocation efficace de la multitude de différentes tâches entre individus demande un ajustement dynamique afin de répondre aux exigences d'un environnement en constant changement. Un nombre considérable de modèles théoriques se sont attachés à identifier les mécanismes permettant aux colonies d'effectuer une allocation efficace des tâches. La grande majorité des ces modèles sont basés sur le constat que les individus d'une même colonie diffèrent dans leur propension (inclination à répondre) à effectuer différentes tâches. Etant donné que les individus possédant un faible seuil de réponse à un stimulus associé à une tâche donnée sont plus disposés à effectuer cette dernière que les individus possédant un seuil élevé, les différences de seuils parmi les individus vivant au sein d'une même colonie mènent à une certaine répartition du travail. Ces modèles théoriques suggèrent que la variation des seuils des individus est affectée par la diversité génétique propre à la colonie. Cependant, ces modèles ne considèrent pas la structure génétique qui est à la base des seuils de réponse individuels. Ceci est très important car une meilleure compréhension de la répartition du travail requière de déterminer de quelle manière les variations génotypiques sont associées aux différentes distributions de seuils de réponse à l'intérieur d'une même colonie. Dans le cadre de cette thèse, nous étudions l'influence combinée de la variabilité génétique d'une colonie (qui prend son origine dans la variation du nombre d'accouplements des reines) avec le nombre de gènes supportant les seuils de réponse, vis-à-vis de la performance de l'allocation des tâches. Nous avons utilisé un simulateur basé sur des agents pour modéliser une situation où les travailleurs d'une colonie devaient accomplir une tâche de régulation (1a quantité d'une nourriture donnée doit être maintenue à l'intérieur d'un certain intervalle) ou une tâche de recherche de nourriture (la quantité d'une certaine nourriture doit être accumulée autant que possible). Dans ce contexte, 'efficacité des colonies tient en partie des travailleurs qui sont capable d'effectuer les deux tâches de manière efficace. Pour étudier l'effet de la diversité génétique d'une colonie, nous comparons l'efficacité des colonies possédant des reines qui s'accouplent avec un nombre variant de mâles. D'autre part, l'influence de la structure génétique a été étudiée en variant le nombre de loci à la base du seuil de réponse des deux tâches de régulation et de recherche de nourriture. Une évolution artificielle a été réalisée pour évoluer les valeurs alléliques qui sont à l'origine de ces seuils de réponse. Les résultats ont révélé que de nombreux accouplements se traduisaient toujours en une plus grande performance de la colonie, quelque soit le nombre de loci encodant les seuils des tâches de régulation et de recherche de nourriture. Cependant, les effets bénéfiques d'accouplements additionnels ont été particulièrement important lorsque la structure génétique des reines comprenait un ou quelques gènes pour le seuil de réponse pour la tâche de recherche de nourriture. D'autre part, un nombre plus élevé de gènes encodant la tâche de recherche de nourriture a diminué la performance de la colonie avec un effet nuisible d'autant plus fort lorsque les reines s'accouplent avec plusieurs mâles. Finalement, le nombre de gènes déterminant le seuil pour la tâche de régulation eu seulement un effet mineur mais incrémental sur la performance de la colonie. Pour conclure, nos expériences numériques révèlent l'importance de considérer les effets associés à la fréquence d'accouplement des reines, à la structure génétique qui est à l'origine des seuils de réponse pour les tâches ainsi qu'au type de tâche effectué au moment d'étudier les facteurs qui régulent l'efficacité de la répartition du travail chez les insectes vivant en communauté. Dans cette thèse, nous étudions l'efficacité de l'allocation des tâches des modèles prenant en compte des seuils de réponses, et les comparons à des réseaux de neurones. Alors que les modèles basés sur des seuils de réponse sont couramment utilisés parmi les biologistes intéressés par la répartition des tâches chez les insectes vivant en société, notre simulation montre qu'ils se révèlent peu efficace comparé à un modèle faisant usage de réseaux de neurones. Un point faible majeur des seuils de réponse est qu'ils échouent sur un point crucial nécessaire à la répartition des tâches, la capacité des individus d'une colonie à commuter efficacement entre des tâches soumises à des conditions environnementales changeantes. De plus, les propriétés intrinsèques des modèles basés sur l'utilisation de seuils conduisent à de larges populations de travailleurs inactifs. Nos résultats mettent en évidence les limites de ces modèles basés sur l'utilisation de seuils et fournissent un substitut adéquat. Ensemble, les expériences présentées dans cette thèse fournissent de nouvelles contributions pour comprendre comment la répartition du travail chez les insectes vivant en société est influencée par la fréquence d'accouplements des reines ainsi que par la structure génétique qui est à l'origine, pour un travailleur, du seuil de réponse pour une tâche. De plus, cette thèse fournit également un nouveau modèle décrivant les mécanismes qui sont à l'origine de l'allocation des tâches entre travailleurs, mécanismes qui peuvent être appliqué de manière plus générale que ceux couramment utilisés et basés sur des seuils de réponse.

Task-dependent influence of genetic architecture and mating frequency on division of labour in social insect societies.

Division of labour is one of the most prominent features of social insects. The efficient allocation of individuals to different tasks requires dynamic adjustment in response to environmental perturbations. Theoretical models suggest that the colony-level flexibility in responding to external changes and internal perturbation may depend on the within-colony genetic diversity, which is affected by the number of breeding individuals. However, these models have not considered the genetic architecture underlying the propensity of workers to perform the various tasks. Here, we investigated how both within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes influencing the stimulus (threshold) for a given task at which workers begin to perform that task jointly influence task allocation efficiency. We used a numerical agent-based model to investigate the situation where workers had to perform either a regulatory task or a foraging task. One hundred generations of artificial selection in populations consisting of 500 colonies revealed that an increased number of matings always improved colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or a few genes for the foraging task's threshold. By contrast, a higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes encoding the threshold for the regulatory task only had a minor effect on colony performance. Overall, our numerical experiments support the importance of mating frequency on efficiency of division of labour and also reveal complex interactions between the number of matings and genetic architecture.

What makes articles highly cited?

We examined drivers of article citations using 776 articles that were published from 1990-2012 in a broad-based and high-impact social sciences journal, The Leadership Quarterly. These articles had 1,191 unique authors having published and received in total (at the time of their most recent article published in our dataset) 16,817 articles and 284,777 citations, respectively. Our models explained 66.6% of the variance in citations and showed that quantitative, review, method, and theory articles were significantly more cited than were qualitative articles or agent-based simulations. As concerns quantitative articles, which constituted the majority of the sample, our model explained 80.3% of the variance in citations; some methods (e.g., use of SEM) and designs (e.g., meta-analysis), as well as theoretical approaches (e.g., use of transformational, charismatic, or visionary type-leadership theories) predicted higher article citations. Regarding the statistical conclusion validity of quantitative articles, articles having endogeneity threats received significantly fewer citations than did those using a more robust design or an estimation procedure that ensured correct causal estimation. We make several general recommendations on how to improve research practice and article citations.

Transition to parenthood: The role of social interaction and endogenous networks

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Merkel cells and the individuality of friction ridge skin

There is no definite theory yet for the mechanism by which the pattern of epidermal ridges on fingers, palms and soles forming friction ridge skin (FRS) patterns is created. For a long time growth forces in the embryonal epidermis have been believed to be involved in FRS formation. More recent evidence suggests that Merkel cells play an important part in this process as well. Here we suggest a model for the formation of FRS patterns that links Merkel cells to the epidermal stress distribution. The Merkel cells are modeled as agents in an agent based model that move anisotropically where the anisotropy is created by the epidermal stress tensor. As a result ridge patterns are created with pattern defects as they occur in real FRS patterns. As a consequence we suggest why the topology of FRS patterns is indeed unique as the arrangement of pattern defects is sensitive to the initial configuration of Merkel cells.

Statistical mechanics of multi-edge networks

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.

On learning dynamics underlying the evolution of learning rules.

In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.

Modeling the Emergence of Social Structure from a Phylogenetic Point of View

Based on provious (Hemelrijk 1998; Puga-González, Hildenbrant & Hemelrijk 2009), we have developed an agent-based model and software, called A-KinGDom, which allows us to simulate the emergence of the social structure in a group of non-human primates. The model includes dominance and affiliative interactions and incorporate s two main innovations (preliminary dominance interactions and a kinship factor), which allow us to define four different attack and affiliative strategies. In accordance with these strategies, we compared the data obtained under four simulation conditions with the results obtained in a provious study (Dolado & Beltran 2012) involving empirical observations of a captive group of mangabeys (Cercocebus torquatus)

An index for quantifying flocking behavior

One of the classic research topics in adaptive behavior is the collective displacement of groups of organisms such as flocks of birds, schools of fish, herds of mammals and crowds of people. However, most agent-based simulations of group behavior do not provide a quantitative index for determining the point at which the flock emerges. We have developed an index of the aggregation of moving individuals in a flock and have provided an example of how it can be used to quantify the degree to which a group of moving individuals actually forms a flock.

Statistical mechanics of multi-edge networks

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.

The role of gadoxetic acid as a paramagnetic contrast medium in the characterization and detection of focal liver lesions: a review

Recent studies have demonstrated that the use of paramagnetic hepatobiliary contrast agents in the acquisition of magnetic resonance images remarkably improves the detection and differentiation of focal liver lesions, as compared with extracellular contrast agents. Paramagnetic hepatobiliary contrast agents initially show the perfusion of the lesions, as do extracellular agents, but delayed contrast-enhanced images can demonstrate contrast uptake by functional hepatocytes, providing further information for a better characterization of the lesions. Additionally, this intrinsic characteristic increases the accuracy in the detection of hepatocellular carcinomas and metastases, particularly the small-sized ones. Recently, a hepatobiliary contrast agent called gadolinium ethoxybenzyl dimeglumine, that is simply known as gadoxetic acid, was approved by the National Health Surveillance Agency for use in humans. The authors present a literature review and a practical approach of magnetic resonance imaging utilizing gadoxetic acid as contrast agent, based on patients' images acquired during their initial experiment.

Tuotantofilosofiat

Työssä esitellään käytetyimpiä tuotantofilosofioita. Tuotantofilosofia on hyvin laaja käsite ja sen vuoksi myös jotkin esiteltävistä menetelmistä ovat hyvin kaukana toisistaan. Työ koostuu teoriaosiosta, jossa on esitelty kukin tuotantofilosofia ja lopuksi johtopäätöksiä-osiossa käsitellään sitä, kuinka menetelmät liittyvät toisiinsa. Työssä esitellään JIT/JOT-tuotanto, Lean-tuotanto, Monozukuri, Modulointi, Standardointi, Strategiatyö, Six Sigma, TQM, TPM, QFD, MFD, Simulointi, Digitaalinen valmistus, DFX ja ns. uudet tuotantofilosofiat. Eri menetelmistä löytyvää lähdemateriaalia on tarjolla monipuolisesti, josta johtuen menetelmistä on voitu esitellä vain pääpiirteet. Tuotantofilosofioiden avulla voidaan saavuttaa monia eri asioita. Osa menetelmistä on luotu tuotannon tehostamiseksi ja yksinkertaistamiseksi, osa puolestaan lisää tuotannon tai koko yrityksen laatutasoa ja osa puolestaan helpottaa tuotteiden suunnittelu-työtä. Moni esiteltävistä filosofioista ei istu yksinomaan yhteen edellä mainituista kategorioista vaan kattaa laajempia alueita pitäen sisällään jopa kaikkia kolmea mainittua tulosta. Näiden lisäksi työssä on esitelty lyhyesti uusia tuotantofilosofioita, jotka ovat hieman irrallisia kokonaisuuksia verrattuna muihin työssä esiteltäviin filosofioihin. Työn tarkoituksena on auttaa hahmottamaan suurta kokonaisuutta jonka tuotantofilosofiat tuottavat. On tärkeää osata hahmottaa filosofioiden riippuvuus toisistaan ja se, että otettaessa käyttöön jotain tuotantofilosofiaa, tarkoittaa se myös mahdollisesti monen muunkin asian huomioonottamista. Tätä näkökantaa selvennetään johtopäätöksissä.

Disruptive innovations at the bottom of the pyramid : can they impact the sustainability of today´s top companies?

Due to the different dynamics required for organizations to serve the emerging market which contains billions of people at the bottom of the pyramid (BOP) coupled with the increasing desire for organizations to grow and be more multinational, organizations need to continually innovate. However, the tendency for large and established companies to ignore the BOP market and rather focus on existing markets, gives an indication of the existence of a vulnerability that potentially disruptive innovations from the BOP will not be recognized in good time for a counter measure. This can be deduced from the fact that good management practice advocates that managers should learn and listen to their customers. Therefore majority of the large existing companies continually focus on their main customer/market with sustaining innovations which leaves aspiring new entrants with an underserved BOP market to experiment with. With the aid of research interviews and an agent-based model (ABM) simulation, this thesis examines the attributes of BOP innovations that can qualify them as disruptive and the possibilities of tangible disruptive innovations arising from the bottom of the pyramid and their underlying drivers. The thesis Furthermore, examines the associated impact of such innovations on the future sustainability of established large companies that are operating in the developed world, particularly those with a primary focus which is targeted towards the market at the top of the pyramid (TOP). Additionally, with the use of a scenario planning model, the research provides an evaluation of the possible evolution and potential sustainability impacts that could emerge, from the interplay of innovations at the two pyramidal market levels and the chosen market focus of organizations – TOP or BOP. Using four scenario quadrants, the thesis demonstrates the resulting possibilities from the interaction between the rate of innovations and the segment focused on by organizations with disruptive era characterizing the paradigm shift quadrant. Furthermore, a mathematical model and two theoretical propositions are developed for further research. As recommendations, the thesis also extends the ambidextrous organizational theory, business model innovation and portfolio diversification as plausible recommendations to limit a catastrophic impact, resulting from disruptive innovations.

From network pictures to network insight in solution business – the role of internal communication

Operating in business-to-business markets requires an in-depth understanding on business networks. Actions and reactions made to compete in markets are fundamentally based on managers‘ subjective perceptions of the network. However, an amalgamation of these individual perceptions, termed a network picture, to a common company level shared understanding on that network, known as network insight, is found to be a substantial challenge for companies. A company‘s capability to enhance common network insight is even argued to lead competitive advantage. Especially companies with value creating logics that require wide comprehension of and collaborating in networks, such as solution business, are necessitated to develop advanced network insight. According to the extant literature, dispersed pieces of atomized network pictures can be unified to a common network insight through a process of amalgamation that comprises barriers/drivers of multilateral exchange, manifold rationality, and recursive time. However, the extant body of literature appears to lack an understanding on the role of internal communication in the development of network insight. Nonetheless, the extant understanding on the amalgamation process indicates that internal communication plays a substantial role in the development of company level network insight. The purpose of the present thesis is to enhance understanding on internal communication in the amalgamation of network pictures to develop network insight in the solution business setting, which was chosen to represent business-to-business value creating logic that emphasizes the capability to understand and utilize networks. Thus, in solution business the role of succeeding in the amalgamation process is expected to emphasize. The study combines qualitative and quantitative research by means of various analytical methods including multiple case analysis, simulation, and social network analysis. Approaching the nascent research topic with differing perspectives and means provides a broader insight on the phenomenon. The study provides empirical evidence from Finnish business-to-business companies which operate globally. The empirical data comprise interviews (n=28) with managers of three case companies. In addition the data includes a questionnaire (n=23) collected mainly for the purpose of social network analysis. In addition, the thesis includes a simulation study more specifically achieved by means of agent based modeling. The findings of the thesis shed light on the role of internal communication in the amalgamation process, contributing to the emergent discussion of network insights and thus to the industrial marketing research. In addition, the thesis increases understanding on internal communication in the change process to solution business, a supplier‘s internal communication in its matrix organization structure during a project sales process, key barriers and drivers that influence internal communication in project sales networks, perceived power within industrial project sales, and the revisioning of network pictures. According to the findings, internal communication is found to play a substantial role in the amalgamation process. First, it is suggested that internal communication is a base of multilateral exchange. Second, it is suggested that internal communication intensifies and maintains manifold rationality. Third, internal communication is needed to explicate the usually differing time perspectives of others and thus it is suggested that internal communication has role as the explicator of recursive time. Furthermore, the role of an efficient amalgamation process is found to be emphasized in solutions business as it requires a more advanced network insight for cross-functional collaboration. Finally, the thesis offers several managerial implications for industrial suppliers to enhance the amalgamation process when operating in solution business.

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.